Pub Date : 2024-03-14DOI: 10.1177/15344843241239723
Andreas Wallo, Daniel Lundqvist, Alan Coetzer
Recent societal challenges highlight the importance of learning in organizations. Nurturing employee learning requires leaders who prioritize learning-oriented leadership. While many studies have used qualitative methods to study how this leadership is performed in daily work, there have been no previous attempts to synthesize this body of research. This paper presents a framework based on a review of 38 qualitative papers on how leaders facilitate workplace learning. The framework identifies two elements of leadership: direct leadership behaviors, which involve supporting, educating, making demands, and role modelling, and indirect leadership behaviors, which facilitate learning through building a learning climate, influencing work organization, freeing up resources for learning, and encouraging knowledge dissemination. The review finds that situational factors shape learning-oriented leadership, and that this leadership involves the deployment of activities located on a planned-spontaneous continuum to facilitate learning. Longitudinal studies across professional groups and contexts will deepen our understanding of this concept.
{"title":"Learning-Oriented Leadership in Organizations: An Integrative Review of Qualitative Studies","authors":"Andreas Wallo, Daniel Lundqvist, Alan Coetzer","doi":"10.1177/15344843241239723","DOIUrl":"https://doi.org/10.1177/15344843241239723","url":null,"abstract":"Recent societal challenges highlight the importance of learning in organizations. Nurturing employee learning requires leaders who prioritize learning-oriented leadership. While many studies have used qualitative methods to study how this leadership is performed in daily work, there have been no previous attempts to synthesize this body of research. This paper presents a framework based on a review of 38 qualitative papers on how leaders facilitate workplace learning. The framework identifies two elements of leadership: direct leadership behaviors, which involve supporting, educating, making demands, and role modelling, and indirect leadership behaviors, which facilitate learning through building a learning climate, influencing work organization, freeing up resources for learning, and encouraging knowledge dissemination. The review finds that situational factors shape learning-oriented leadership, and that this leadership involves the deployment of activities located on a planned-spontaneous continuum to facilitate learning. Longitudinal studies across professional groups and contexts will deepen our understanding of this concept.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"20 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140152663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-25DOI: 10.1177/15344843231224009
Kelechi Ekuma
This systematic review synthesizes the existing literature on the impact of artificial intelligence (AI) and automation on Human Resource Development (HRD) practices and outcomes. The study explores how AI and automation affect HRD, highlighting specific HRD processes affected and their influence on outcomes. A comprehensive search was conducted across academic databases, HRD journals, and conference proceedings, resulting in a selection of relevant studies. The findings were analyzed through a narrative synthesis, with subgroup analyses based on specific HRD processes. The review provides insights into AI and automation implications for HRD researchers and practitioners. It also identifies research gaps and future directions.
{"title":"Artificial Intelligence and Automation in Human Resource Development: A Systematic Review","authors":"Kelechi Ekuma","doi":"10.1177/15344843231224009","DOIUrl":"https://doi.org/10.1177/15344843231224009","url":null,"abstract":"This systematic review synthesizes the existing literature on the impact of artificial intelligence (AI) and automation on Human Resource Development (HRD) practices and outcomes. The study explores how AI and automation affect HRD, highlighting specific HRD processes affected and their influence on outcomes. A comprehensive search was conducted across academic databases, HRD journals, and conference proceedings, resulting in a selection of relevant studies. The findings were analyzed through a narrative synthesis, with subgroup analyses based on specific HRD processes. The review provides insights into AI and automation implications for HRD researchers and practitioners. It also identifies research gaps and future directions.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"22 3","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139157484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.1177/15344843231217181
Jae Young Lee, Y. Lee
Although people analytics is a fast-emerging field with importance to HRD, HRD researchers still lack a comprehensive understanding of it. This study examines the current body of knowledge in people analytics through the lens of human resource (HR) development by performing an integrative literature review of 91 articles. This study identifies five categories of knowledge: (1) definitions and boundaries of terms, (2) building blocks of people analytics in organizations, (3) types of analytics, (4) ethical issues related to people analytics, and (5) applications of people analytics to the HRD field. This study makes theoretical and practical contributions to the field of HR development by exploring the current state of people analytics and people analytics’ application to HR development practice. It also enhances scholars’ understanding of people analytics within HR development boundaries and provides insights for future research. Finally, this study provides practical guidance for HR development practitioners seeking to leverage people analytics in their work.
{"title":"Integrative Literature Review on People Analytics and Implications From the Perspective of Human Resource Development","authors":"Jae Young Lee, Y. Lee","doi":"10.1177/15344843231217181","DOIUrl":"https://doi.org/10.1177/15344843231217181","url":null,"abstract":"Although people analytics is a fast-emerging field with importance to HRD, HRD researchers still lack a comprehensive understanding of it. This study examines the current body of knowledge in people analytics through the lens of human resource (HR) development by performing an integrative literature review of 91 articles. This study identifies five categories of knowledge: (1) definitions and boundaries of terms, (2) building blocks of people analytics in organizations, (3) types of analytics, (4) ethical issues related to people analytics, and (5) applications of people analytics to the HRD field. This study makes theoretical and practical contributions to the field of HR development by exploring the current state of people analytics and people analytics’ application to HR development practice. It also enhances scholars’ understanding of people analytics within HR development boundaries and provides insights for future research. Finally, this study provides practical guidance for HR development practitioners seeking to leverage people analytics in their work.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"64 6","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-02DOI: 10.1177/15344843231217174
Doo Hun Lim, Jae Young Lee, Sunyoung Park
This study reviews the potential applications of the metaverse to various areas of human resource development (HRD) and reflects on the applications’ significance for employee and organizational development. Adopting a narrative review approach to this study, we selected and reviewed 34 cases. From our review, we found several findings that contributes to the HRD field in several ways. First, it draws the attention of HRD researchers and practitioners to a critical emerging trend that has been overlooked in the field. Second, it offers an analytical view of the metaverse in comparison to other training or learning technologies, assessing its effectiveness in employee development. Third, this study enhances the perspectives of HRD researchers and practitioners regarding this new technology by providing practical and theoretical insights into how metaverse-based interventions can reshape organizational culture and improve employee performance in the workplace. Lastly, it addresses compelling theoretical and practical questions related to HRD issues arising from the metaverse.
{"title":"The Metaverse in the Workplace: Possibilities and Implications for Human Resource Development","authors":"Doo Hun Lim, Jae Young Lee, Sunyoung Park","doi":"10.1177/15344843231217174","DOIUrl":"https://doi.org/10.1177/15344843231217174","url":null,"abstract":"This study reviews the potential applications of the metaverse to various areas of human resource development (HRD) and reflects on the applications’ significance for employee and organizational development. Adopting a narrative review approach to this study, we selected and reviewed 34 cases. From our review, we found several findings that contributes to the HRD field in several ways. First, it draws the attention of HRD researchers and practitioners to a critical emerging trend that has been overlooked in the field. Second, it offers an analytical view of the metaverse in comparison to other training or learning technologies, assessing its effectiveness in employee development. Third, this study enhances the perspectives of HRD researchers and practitioners regarding this new technology by providing practical and theoretical insights into how metaverse-based interventions can reshape organizational culture and improve employee performance in the workplace. Lastly, it addresses compelling theoretical and practical questions related to HRD issues arising from the metaverse.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"15 8","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138606874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-17DOI: 10.1177/15344843231215380
Sangok Yoo, John Turner, Kim Nimon, Bisola Adepoju
The multidimensional characteristic of learning has received little attention in the network literature, resulting in fragmented empirical evidence on learning networks. To address this gap, we introduce a framework that allows a better understanding of the multidimensionality of learning networks by employing the concept of multiplexity in the network literature. Our proposed conceptual framework for multiplex learning networks includes a 3-E typology (exploration, exploitation, and exaptation), which serve as distinct layers within the multiplex networks. We also provide a hypothetical scenario to demonstrate the potential of our multiplex learning networks framework for HRD scholars and practitioners. Moreover, we extend our framework to a multilevel model that connects individual-level learning relationships to team-level relationships. Our framework’s theoretical and practical implications are discussed, and future research directions are suggested.
{"title":"Weaving Layers of Learning: Multiplex Learning Networks in the Workplace","authors":"Sangok Yoo, John Turner, Kim Nimon, Bisola Adepoju","doi":"10.1177/15344843231215380","DOIUrl":"https://doi.org/10.1177/15344843231215380","url":null,"abstract":"The multidimensional characteristic of learning has received little attention in the network literature, resulting in fragmented empirical evidence on learning networks. To address this gap, we introduce a framework that allows a better understanding of the multidimensionality of learning networks by employing the concept of multiplexity in the network literature. Our proposed conceptual framework for multiplex learning networks includes a 3-E typology (exploration, exploitation, and exaptation), which serve as distinct layers within the multiplex networks. We also provide a hypothetical scenario to demonstrate the potential of our multiplex learning networks framework for HRD scholars and practitioners. Moreover, we extend our framework to a multilevel model that connects individual-level learning relationships to team-level relationships. Our framework’s theoretical and practical implications are discussed, and future research directions are suggested.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"15 4","pages":""},"PeriodicalIF":6.4,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139264717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1177/15344843231213205
Thomas Garavan
{"title":"Editorial: Mapping the Next Phase of Growth for HRDR","authors":"Thomas Garavan","doi":"10.1177/15344843231213205","DOIUrl":"https://doi.org/10.1177/15344843231213205","url":null,"abstract":"","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"25 1","pages":"475 - 493"},"PeriodicalIF":6.4,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139294204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.1177/15344843231209362
Seung Won Yoon, Seung-hyun Han, Chungil Chae
This study provides a comprehensive examination of the current research landscape of People Analytics (PA) from Human Resource Development (HRD) perspectives. By leveraging the methodologies of bibliometrics and topic modeling, the paper aims to illuminate key trends and emerging themes. By conducting a comparative analysis of topics and grouped themes from topic modeling and clusters from bibliocoupling, the study reveals a convergence in research focuses. This convergence is particularly evident in areas such as workforce planning and management, data-informed decision-making, applying analytics to various HR functions, and emphasizing the ethical and societal implications of data analytics in HR. The paper also identifies gaps and future research needs for HRD research in the current PA landscape and discusses fertile grounds for future research.
{"title":"People Analytics and Human Resource Development – Research Landscape and Future Needs Based on Bibliometrics and Scoping Review","authors":"Seung Won Yoon, Seung-hyun Han, Chungil Chae","doi":"10.1177/15344843231209362","DOIUrl":"https://doi.org/10.1177/15344843231209362","url":null,"abstract":"This study provides a comprehensive examination of the current research landscape of People Analytics (PA) from Human Resource Development (HRD) perspectives. By leveraging the methodologies of bibliometrics and topic modeling, the paper aims to illuminate key trends and emerging themes. By conducting a comparative analysis of topics and grouped themes from topic modeling and clusters from bibliocoupling, the study reveals a convergence in research focuses. This convergence is particularly evident in areas such as workforce planning and management, data-informed decision-making, applying analytics to various HR functions, and emphasizing the ethical and societal implications of data analytics in HR. The paper also identifies gaps and future research needs for HRD research in the current PA landscape and discusses fertile grounds for future research.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"11 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135366860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-18DOI: 10.1177/15344843231207220
Thomas H. Rasmussen, Mike Ulrich, Dave Ulrich
In this paper we take stock of the current state of People Analytics and identify ways to increase business impact. We suggest a fourth wave of people analytics, which focuses on impact in MY company, not compared to someone else (benchmarking, reporting), not just mimicking someone else (best practice), and not being enamored with the research methodologies (predictive analytics). This pivots people analytics towards answering questions of value to your key stakeholders (employees, senior management and boards inside and investors, customers and communities outside the organization) instead of questions mostly relevant to HR professionals or regulators. We outline a guidance framework for how people analytics can help shape practical solutions for your company to outperform in areas relevant for you. We argue a focus on guidance will amplify the business impact of people analytics, making it more relevant for management actions.
{"title":"Moving People Analytics From Insight to Impact","authors":"Thomas H. Rasmussen, Mike Ulrich, Dave Ulrich","doi":"10.1177/15344843231207220","DOIUrl":"https://doi.org/10.1177/15344843231207220","url":null,"abstract":"In this paper we take stock of the current state of People Analytics and identify ways to increase business impact. We suggest a fourth wave of people analytics, which focuses on impact in MY company, not compared to someone else (benchmarking, reporting), not just mimicking someone else (best practice), and not being enamored with the research methodologies (predictive analytics). This pivots people analytics towards answering questions of value to your key stakeholders (employees, senior management and boards inside and investors, customers and communities outside the organization) instead of questions mostly relevant to HR professionals or regulators. We outline a guidance framework for how people analytics can help shape practical solutions for your company to outperform in areas relevant for you. We argue a focus on guidance will amplify the business impact of people analytics, making it more relevant for management actions.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135882924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.1177/15344843231205066
Eunbi Sim, Shinhee Jeong
This study critically reviews intersectional research (IR) published in the Academy of Human Resource Development (AHRD) journals and presents a framework for future work in IR. First, we identified 10 IR approaches from previous literature and classified them into four perspectives: conceptual, category-based, alternative philosophy-based, and alternative analysis-based perspectives. Utilizing the framework, we found that the majority of IR in HRD has (a) drawn on an intra-categorical approach, (b) focused on the intersection of gender and race, (c) centered on the United States context, and (d) depended on qualitative research methodology. We also examined the IR trends in HRD over time and observed that IR has recently incorporated more diverse approaches and identities and has explored some non-US contexts. To advance IR and better understand the complexity of intersectionality at work, future research needs to continue diversifying research approaches, methods, subjects, and contexts.
{"title":"Mapping the Future of Intersectional Research in Human Resource Development: An Integrated Literature Review","authors":"Eunbi Sim, Shinhee Jeong","doi":"10.1177/15344843231205066","DOIUrl":"https://doi.org/10.1177/15344843231205066","url":null,"abstract":"This study critically reviews intersectional research (IR) published in the Academy of Human Resource Development (AHRD) journals and presents a framework for future work in IR. First, we identified 10 IR approaches from previous literature and classified them into four perspectives: conceptual, category-based, alternative philosophy-based, and alternative analysis-based perspectives. Utilizing the framework, we found that the majority of IR in HRD has (a) drawn on an intra-categorical approach, (b) focused on the intersection of gender and race, (c) centered on the United States context, and (d) depended on qualitative research methodology. We also examined the IR trends in HRD over time and observed that IR has recently incorporated more diverse approaches and identities and has explored some non-US contexts. To advance IR and better understand the complexity of intersectionality at work, future research needs to continue diversifying research approaches, methods, subjects, and contexts.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135131833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-11DOI: 10.1177/15344843231200930
Yu-Ling Chang, Jie Ke
Series of reports on AI misconduct from multiple renowned organizations have triggered a surge of public awareness, calling for more responsible and sustainable use of AI. Noting socially responsible AI (SRAI) as a new concept in the field of PA and HRD, we delved into the subject through an integrative literature review of 75 articles and incorporated three sustainability concepts into AI-enabled PA: corporate social responsibility (CSR), environment, social, and governance (ESG), and UN sustainable development goals (SDGs). Through a stakeholder view, we identified major SRAI stakeholders (subjects) and analyzed their essential considerations (objectives), the impediments of AI technology (causes), and the solutions (means). The analysis illuminated key requirements and considerations for enhancing AI-enabled PA to SRAI-empowered PA towards sustainability. Moreover, we proposed a holistic framework to thoroughly understand SRAI in theory and provided practical implications, recommendations, and future research directions for HRD scholars and professionals.
{"title":"Socially Responsible Artificial Intelligence Empowered People Analytics: A Novel Framework Towards Sustainability","authors":"Yu-Ling Chang, Jie Ke","doi":"10.1177/15344843231200930","DOIUrl":"https://doi.org/10.1177/15344843231200930","url":null,"abstract":"Series of reports on AI misconduct from multiple renowned organizations have triggered a surge of public awareness, calling for more responsible and sustainable use of AI. Noting socially responsible AI (SRAI) as a new concept in the field of PA and HRD, we delved into the subject through an integrative literature review of 75 articles and incorporated three sustainability concepts into AI-enabled PA: corporate social responsibility (CSR), environment, social, and governance (ESG), and UN sustainable development goals (SDGs). Through a stakeholder view, we identified major SRAI stakeholders (subjects) and analyzed their essential considerations (objectives), the impediments of AI technology (causes), and the solutions (means). The analysis illuminated key requirements and considerations for enhancing AI-enabled PA to SRAI-empowered PA towards sustainability. Moreover, we proposed a holistic framework to thoroughly understand SRAI in theory and provided practical implications, recommendations, and future research directions for HRD scholars and professionals.","PeriodicalId":51474,"journal":{"name":"Human Resource Development Review","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135938587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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