Green Human Resource Management Practices' Impact on Employee Green Behaiour Directly and Indirectly Through Enironmental Knowledge and Self Efficacy in the Hotel Industry of Malysia
DOI:
https://doi.org/10.71317/jgst.2.9(s).2026.571Keywords:
Green Human Resource Management (GHRM), Employee Green Behavior (EGB), Environmental Knowledge, Green Self-Efficacy, Hotel Industry, Malaysia, PLS-SEMAbstract
This study investigates the direct and indirect impacts of Green Human Resource Management (GHRM) practices on Employee Green Behavior (EGB) within the Malaysian hotel industry, specifically examining the mediating roles of Environmental Knowledge (EK) and Green Self-Efficacy (SE). Grounded in Social Cognitive Theory, the research addresses a critical gap in the literature by unpacking the cognitive and psychological mechanisms that translate organizational green policies into individual sustainable actions. Employing a quantitative, cross-sectional research design, data were collected from 312 non-managerial and supervisory employees across 3- to 5-star hotels in major Malaysian hospitality hubs. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that GHRM practices exert a significant direct positive influence on EGB. Furthermore, the analysis confirms that both EK and SE serve as crucial partial mediators in this relationship. Notably, GHRM strongly predicts both mediators, with SE emerging as a slightly stronger mediator than EK, highlighting that an employee's psychological belief in their green capabilities is just as critical as their factual knowledge. Theoretically, this study extends the application of Social Cognitive Theory to a developing economy context. Practically, it advises Malaysian hoteliers to avoid superficial "greenwashing" by strategically aligning human capital with sustainability goals through pro-environmental recruitment, interactive confidence-building training, and the formal integration of green KPIs into performance appraisals and reward systems.
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Copyright (c) 2026 Bilal Arif, Badar un Nisa, Aamir Mansoor (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.



