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

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

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.

Keywords: Green human resource management; KNIME; Latent semantic analysis; Network analysis; TF-IDF; Text mining; VOSviewer.

MeSH terms

  • Data Mining*
  • Databases, Factual
  • Humans
  • Publications*
  • Workforce