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绿色人力资源管理的最新趋势：文本挖掘和网络分析。

Recent trends of green human resource management: Text mining and network analysis.

机构信息

Chitkara University, Solan, Himachal Pradesh, India.

Chitkara Business School, Chitkara University, Rajpura, Punjab, India.

出版信息

Environ Sci Pollut Res Int. 2022 Dec;29(56):84916-84935. doi: 10.1007/s11356-022-21471-9. Epub 2022 Jul 5.

DOI:10.1007/s11356-022-21471-9
PMID:35790632
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9255839/
Abstract

Issues of the environmental crisis are being addressed by researchers, government, and organizations alike. GHRM is one such field that is receiving lots of research focus since it is targeted at greening the firms and making them eco-friendly. This research reviews 317 articles from the Scopus database published on green human resource management (GHRM) from 2008 to 2021. The study applies text mining, latent semantic analysis (LSA), and network analysis to explore the trends in the research field in GHRM and establish the relationship between the quantitative and qualitative literature of GHRM. The study has been carried out using KNIME and VOSviewer tools. As a result, the research identifies five recent research trends in GHRM using K-mean clustering. Future researchers can work upon these identified trends to solve environmental issues, make the environment eco-friendly, and motivate firms to implement GHRM in their practices.

摘要

环境危机问题正受到研究人员、政府和各类组织的关注。人力资源管理（HRM）是一个受到大量研究关注的领域，因为它旨在使企业环保化、生态友好化。本研究回顾了 2008 年至 2021 年期间在 Scopus 数据库上发表的关于绿色人力资源管理（GHRM）的 317 篇文章。本研究采用文本挖掘、潜在语义分析（LSA）和网络分析来探索 GHRM 研究领域的趋势，并建立 GHRM 的定量和定性文献之间的关系。该研究使用了 KNIME 和 VOSviewer 工具。结果，研究使用 K-均值聚类识别了 GHRM 中的五个近期研究趋势。未来的研究人员可以在这些已确定的趋势基础上开展工作，以解决环境问题，使环境生态友好，并激励企业在实践中实施 GHRM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/0fe92b134a33/11356_2022_21471_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/b48cebf5837c/11356_2022_21471_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/4eed691e9e6c/11356_2022_21471_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/72b699edb011/11356_2022_21471_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/12e2acf7be38/11356_2022_21471_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/91bf5a1c11cd/11356_2022_21471_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/0ffadc772033/11356_2022_21471_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/d8a9b639ec7d/11356_2022_21471_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/0fe92b134a33/11356_2022_21471_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/b48cebf5837c/11356_2022_21471_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/f3d68a8ed999/11356_2022_21471_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/9d0afb667fbf/11356_2022_21471_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/250247d66bd5/11356_2022_21471_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/4eed691e9e6c/11356_2022_21471_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/72b699edb011/11356_2022_21471_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/12e2acf7be38/11356_2022_21471_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/91bf5a1c11cd/11356_2022_21471_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/0ffadc772033/11356_2022_21471_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/d8a9b639ec7d/11356_2022_21471_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd0/9255839/0fe92b134a33/11356_2022_21471_Fig11_HTML.jpg

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