Human Resource Management Review最新文献

{"title":"An interdisciplinary review of AI and HRM: Challenges and future directions","authors":"Yuan Pan ,&nbsp;Fabian J. Froese","doi":"10.1016/j.hrmr.2022.100924","DOIUrl":"10.1016/j.hrmr.2022.100924","url":null,"abstract":"<div><p>Artificial intelligence (AI) has the potential to change the future of human resource management (HRM). Scholars from different disciplines have contributed to the field of AI in HRM but with rather insufficient cross-fertilization, thus leading to a fragmented body of knowledge. In response, we conducted a systematic, interdisciplinary review of 184 articles to provide a comprehensive overview. We grouped prior research into four categories based on discipline: management and economics, computer science, engineering and operations, and others. The findings reveal that studies in different disciplines had different research foci and utilized different methods. While studies in the technical disciplines tended to focus on the development of AI for specific HRM functions, studies from the other disciplines tended to focus on the consequences of AI on HRM, jobs, and labor markets. Most studies in all categories were relatively weak in theoretical development. We therefore offer recommendations for interdisciplinary collaborations, propose a unified definition of AI, and provide implications for research and practice.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100924"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43150628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review and theorization of workplace backlash: Looking back and moving forward through the lens of social dominance theory","authors":"Jin Lee","doi":"10.1016/j.hrmr.2022.100900","DOIUrl":"10.1016/j.hrmr.2022.100900","url":null,"abstract":"<div><p>Workplace backlash, <em>the explicit/implicit, and/or intentional/unintentional attempts to reject efforts to promote diversity, taken by both dominant and subordinate social group members to maintain the group-based social hierarchy at work</em><span>, has emerged as a major threat to fostering diversity and inclusiveness in the workplace. Although intense scholarly attention has been paid to workplace backlash, the literature has a highly individualistic and fragmented perspective of backlash, which hinders theoretical advancement. As a remedy for conceptual and theoretical heterogeneity, I first conducted a systematic review of the literature to present a critical overview of past scholarly endeavors and take stock of the empirical evidence. This article provides an alternative, unified definition of workplace backlash drawn from intergroup relations and the power hierarchy among social group members. Finally, based on the perspective of group-based social hierarchy, this study describes the emergence, development, and maintenance of workplace backlash through the lens of social dominance theory. Implications and future research suggestions are also discussed.</span></p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100900"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49360401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theorizing the relationship between discretionary employee benefits and individual performance","authors":"David B. Balkin ,&nbsp;Steve Werner","doi":"10.1016/j.hrmr.2022.100901","DOIUrl":"10.1016/j.hrmr.2022.100901","url":null,"abstract":"<div><p>The literature on compensation has devoted little attention to the relationship between discretionary employee benefits and individual performance, perhaps because benefits are allocated equally to large groups of employees, are not tied to individual performance, and are viewed as entitlements. Discretionary benefits include all the benefits an employer provides to employees voluntarily (i.e., not legally required). Employees can use internet search tools to make comparisons between focal and referent firms of their expenditures on discretionary benefits, which can symbolize employer support for employee well-being or invoke perceptions of equity. In our paper, we provide a novel insight into the relationship between discretionary benefits and employee individual performance through a theoretical lens that combines insights from organizational support theory and equity theory shaped by perceptions of social and economic exchange relationships. In our conceptual model we develop theoretical logic that explains that perceived discretionary benefits, moderated by benefits satisfaction and mediated by perceived organizational support and perceived equity, are linked to individual performance. The paper concludes with a discussion of the theoretical implications and directions for future research.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100901"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47923488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inclusive talent development as a key talent management approach: A systematic literature review","authors":"Maniam Kaliannan ,&nbsp;Darshana Darmalinggam ,&nbsp;Magiswary Dorasamy ,&nbsp;Mathew Abraham","doi":"10.1016/j.hrmr.2022.100926","DOIUrl":"https://doi.org/10.1016/j.hrmr.2022.100926","url":null,"abstract":"<div><p>Over the past decades, organizations have faced challenges in retaining good employees due to market competition and talent scarcity, thereby forcing leaders to improve their human resource strategies. Organizations often source exclusive talent development instead of nurturing talent inclusively. Exclusive refers to organizations' tendency to hire top talents outside their organization when needs arise, or if they have to look for candidates within the organization, only those identified as performers within their elite pool are selected. Literature suggests that inclusive talent development (i.e., career development via training for all employees regardless of individual performance) can complement management for employee retention. The present study carries out a systematic review of articles published from 1997 to 2020 pertaining to talent development, particularly inclusive nurturing, to enable frugal human resource management, i.e., developing human resource inclusive talent development (ITD) in a resource constrained environment. We address three major questions: to what degree is talent development (TD) represented in the wider talent management (TM) literature?; how does ITD contribute to individual talent growth and organizational performance?; and what are the limitations of current research on ITD? A total of 48 articles on TD, with 13 articles on ITD, are analyzed to provide theoretical and practical insights. This review presents research gaps on inclusive TD, and highlights future research directions, such as wider coverage to develop a more comprehensive scope, TD for low performers to improve their individual growth and organizational performance, application of frugal innovation through ITD, and association with resource-based view – valuable, rare, inimitability, and organized model (RBV-VRIO). While ITD coupled with other TM activities has significant effect on individual growth and organizational performance, the evidence for and discussion of this concept remains scarce. The research contributes to existing HRM literatures: (1) TD is a limited area of research and has minority representation within TM literature; (2) ITD is becoming increasingly crucial for individual talent growth and organizational performance towards a sustainable competitive advantage as primed by the RBV – VRIO model; and (3) key limitations of research on TD include one-sided perspectives to TD, lack of balance between individual talent growth and organizational performance, and other methodological weaknesses.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100926"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49757964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-augmented HRM: Antecedents, assimilation and multilevel consequences","authors":"Verma Prikshat ,&nbsp;Ashish Malik ,&nbsp;Pawan Budhwar","doi":"10.1016/j.hrmr.2021.100860","DOIUrl":"10.1016/j.hrmr.2021.100860","url":null,"abstract":"<div><p>The current literature on the use of disruptive innovative technologies, such as artificial intelligence (AI) for human resource management (HRM) function, lacks a theoretical basis for understanding. Further, the adoption and implementation of AI-augmented HRM, which holds promise for delivering several operational, relational and transformational benefits, is at best patchy and incomplete. Integrating the technology, organisation and people (TOP) framework with core elements of the theory of innovation assimilation and its impact on a range of AI-Augmented HRM outcomes, or what we refer to as (HRM^(AI)), this paper develops a coherent and integrated theoretical framework of HRM^(AI) assimilation. Such a framework is timely as several post-adoption challenges, such as the dark side of processual factors in innovation assimilation and system-level factors, which, if unattended, can lead to the opacity of AI applications, thereby affecting the success of any HRM^(AI). Our model proposes several testable future research propositions for advancing scholarship in this area. We conclude with implications for theory and practice.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100860"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43077090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Taking the emergent in team emergent states seriously: A review and preview","authors":"Bård Fyhn,&nbsp;Vidar Schei,&nbsp;Therese E. Sverdrup","doi":"10.1016/j.hrmr.2022.100928","DOIUrl":"10.1016/j.hrmr.2022.100928","url":null,"abstract":"<div><p>Team emergent states are properties that develop during team interactions and describe team members' attitudes and feelings (e.g., cohesion). However, these states' emergent nature has largely been neglected, as most studies do not examine the temporality of team phenomena. We review longitudinal studies on team emergent states and demonstrate that a majority of papers reveal their temporal dynamics but offer no universal patterns as to <em>how</em> such states emerge. The review reveals common variables related to temporal dynamics and highlights the importance of studying the development of team emergent states to enhance our knowledge of their causal directions, antecedents, and outcomes. We suggest that future research should clarify the <em>concept</em> of team emergent states, connect <em>theories</em> to research on temporal dynamics, adopt more <em>qualitative</em> approaches to answer “how” and “why” questions, and improve <em>research designs</em> to study meaningful forms of change. Lastly, we present practical implications for the HR field.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100928"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48294519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing a multi-stakeholder perspective on opacity, transparency and strategies to reduce opacity in algorithm-based human resource management","authors":"Markus Langer,&nbsp;Cornelius J. König","doi":"10.1016/j.hrmr.2021.100881","DOIUrl":"10.1016/j.hrmr.2021.100881","url":null,"abstract":"<div><p>Artificial Intelligence and algorithmic technologies support or even automate a large variety of human resource management (HRM) activities. This affects a range of stakeholders with different, partially conflicting perspectives on the opacity and transparency of algorithm-based HRM. In this paper, we explain why opacity is a key characteristic of algorithm-based HRM, describe reasons for opaque algorithm-based HRM, and highlight the implications of opacity from the perspective of the main stakeholders involved (users, affected people, deployers, developers, and regulators). We also review strategies to reduce opacity and promote transparency of algorithm-based HRM (technical solutions, education and training, regulation and guidelines), and emphasize that opacity and transparency in algorithm-based HRM can simultaneously have beneficial and detrimental consequences that warrant taking a multi-stakeholder view when considering these consequences. We conclude with a research agenda highlighting stakeholders' interests regarding opacity, strategies to reduce opacity, and consequences of opacity and transparency in algorithm-based HRM.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100881"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48833555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence–HRM Interactions and Outcomes: A Systematic Review and Causal Configurational Explanation","authors":"Shubhabrata Basu ,&nbsp;Bishakha Majumdar ,&nbsp;Kajari Mukherjee ,&nbsp;Surender Munjal ,&nbsp;Chandan Palaksha","doi":"10.1016/j.hrmr.2022.100893","DOIUrl":"https://doi.org/10.1016/j.hrmr.2022.100893","url":null,"abstract":"<div><p>Artificial intelligence (AI) systems and applications based on them are fast pervading the various functions of an organization. While AI systems enhance organizational performance, thereby catching the attention of the decision makers, they nonetheless pose threats of job losses for human resources. This in turn pose challenges to human resource managers, tasked with governing the AI adoption processes. However, these challenges afford opportunities to critically examine the various facets of AI systems as they interface with human resources. To that end, we systematically review the literature at the intersection of AI and human resource management (HRM). Using the configurational approach, we identify the evolution of different theme based causal configurations in conceptual and empirical research and the outcomes of AI-HRM interaction. We observe incremental mutations in thematic causal configurations as the literature evolves and also provide thematic configuration based explanations to beneficial and reactionary outcomes in the AI-HRM interaction process.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100893"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49746935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes","authors":"Waymond Rodgers ,&nbsp;James M. Murray ,&nbsp;Abraham Stefanidis ,&nbsp;William Y. Degbey ,&nbsp;Shlomo Y. Tarba","doi":"10.1016/j.hrmr.2022.100925","DOIUrl":"10.1016/j.hrmr.2022.100925","url":null,"abstract":"<div><p>Management scholars and practitioners have highlighted the importance of ethical dimensions in the selection of strategies. However, to date, there has been little effort aimed at theoretically understanding the ethical positions of individuals/organizations concerning human resource management (HRM) decision-making processes, the selection of specific ethical positions and strategies, or the post-decision accounting for those decisions. To this end, we present a Throughput model framework that describes individuals' decision-making processes in an algorithmic HRM context. The model depicts how perceptions, judgments, and the use of information affect strategy selection, identifying how diverse strategies may be supported by the employment of certain ethical decision-making algorithmic pathways. In focusing on concerns relating to the impact and acceptance of artificial intelligence (AI) integration in HRM, this research draws insights from multidisciplinary theoretical lenses, such as AI-augmented (HRM^(AI)) and HRM^(AI) assimilation processes, AI-mediated social exchange, and the judgment and choice literature. We highlight the use of algorithmic ethical positions in the adoption of AI for better HRM outcomes in terms of intelligibility and accountability of AI-generated HRM decision-making, which is often underexplored in existing research, and we propose their key role in HRM strategy selection.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100925"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43292333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence and people management: A critical assessment through the ethical lens","authors":"Arup Varma ,&nbsp;Cedric Dawkins ,&nbsp;Kaushik Chaudhuri","doi":"10.1016/j.hrmr.2022.100923","DOIUrl":"https://doi.org/10.1016/j.hrmr.2022.100923","url":null,"abstract":"<div><p>The dramatic increase in the use of Artificial Intelligence (AI) in workplaces around the world has tremendous potential to increase business profitability. While AI has numerous useful applications and can help speed up business processes or transform systems, its use in human resources (HR) processes and systems presents a complex series of ethical considerations that require organizational leaders to tread with caution. In this paper, we argue that as the foremost worker advocates in the firm, HR managers must be ethically sensitive and accountable. They have responsibility to carefully monitor AI programs to ensure that these systems do what they are purported to do and protect the dignity of the worker through transparency regarding the data being collected and privacy regarding its usage. Lastly, the HR manager must closely monitor the fairness and equity impacts of AI such that its use is procedurally and distributivity just.</p></div>","PeriodicalId":48145,"journal":{"name":"Human Resource Management Review","volume":"33 1","pages":"Article 100923"},"PeriodicalIF":11.4,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49746645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}