Exploring Green HRM through Employee Feedback Mining with Information Retrieval and Sentiment Analysis in Tamil Nadu IT Companies

Abstract

This study charts the diffusion of Green Human Resource Management (Green HRM) practices within Tamil Nadu's IT sector using a blended approach that layers augmented text mining over structured employee feedback and emotion-sensitive analytics. Its core aim is to measure the linkage between Green HRM and levels of workplace commitment, alongside a deeper examination of that workforce's weighting of sustainability. Data is captured through a set of standardized Likert-scaled instruments, and the resulting sentiment is then tagged into supportive, indifferent, or critical buckets. This triage isolates the most potent intervention points for Green HRM. Concurrently, a document-extraction pipeline parses open-ended comments to expose Latent Cycles, and a suite of validity tests anchored in correlation and regression assesses the connection of specific Green HRM interventions with behavioral modulation. Findings consistently indicate that Green HRM not only engenders a constructive employee rationale, but it also anchors eco-efficient practices in everyday work routines, thereby accelerating the institution's broader ecological agenda. To deepen the insights, ANOVA and T-test frameworks interrogate employee satisfaction variances, crosscutting demographic strata and uneven corporate maturity in Green HRM adoption. This analysis surfaces statistically significant discrepancies, illustrating how discrete cohorts assimilate Green HRM efforts and, in the process, extending the granularity of the employee engagement narrative.