{"title":"可持续人力资源管理是管理研究的下一个热点?使用主题建模的研究","authors":"Shefali Singh, Kanchan Awasthi, Pradipta Patra, Jaya Srivastava, Shrawan Kumar Trivedi","doi":"10.1108/ijoa-08-2023-3940","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA).</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. The significance of the paper would be in its potential to shed light on emerging areas of interest and provide valuable implications for future research and practice in Sustainable HRM.</p><!--/ Abstract__block -->","PeriodicalId":47017,"journal":{"name":"International Journal of Organizational Analysis","volume":"96 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sustainable HRM the next hotspot for management research? A study using topic modelling\",\"authors\":\"Shefali Singh, Kanchan Awasthi, Pradipta Patra, Jaya Srivastava, Shrawan Kumar Trivedi\",\"doi\":\"10.1108/ijoa-08-2023-3940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA).</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM.</p><!--/ Abstract__block -->\\n<h3>Research limitations/implications</h3>\\n<p>The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM.</p><!--/ Abstract__block -->\\n<h3>Originality/value</h3>\\n<p>By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. 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Sustainable HRM the next hotspot for management research? A study using topic modelling
Purpose
Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018.
Design/methodology/approach
The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA).
Findings
The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM.
Research limitations/implications
The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM.
Originality/value
By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. The significance of the paper would be in its potential to shed light on emerging areas of interest and provide valuable implications for future research and practice in Sustainable HRM.
期刊介绍:
The IJOA welcomes papers that draw on, but not exclusively: ■Organization theory ■Organization behaviour ■Organization development ■Organizational learning ■Strategic and change management ■People in organizational contexts including human resource management and human resource development ■Business and its interrelationship with society ■Ethics and morals, spirituality