Green human resource management practices: a hierarchical model to evaluate the pro-environmental behavior of hotel employees
Notice bibliographique
Résumé
Purpose This paper examines the impact of green human resource management (GHRM) practices on employees’ pro-environmental behavior in Pakistan’s hospitality industry. It attempts to identify the critical success factors involved in promoting GHRM and pro-environmental behaviors at the workplace using Interpretive Structural Modeling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) approaches. Later, based on the ability-motivation-opportunity (AMO) model, the study also categorizes the identified critical factors into three categories: ability, motivation and opportunity. Design/methodology/approach The ISM approach was applied to determine the contextual relationship among the identified critical success factors responsible for promoting GHRM. MICMAC, a structural technique to analyze and validate the ISM-based model, was used to determine the autonomous, dependent, linkage and independent factors based on expert opinions and judgments. The goal was to determine the role of GHRM in transforming the pro-environmental behavior of employees. Findings The study’s findings show that the proper integration of effective GHRM practices significantly impacts pro-environmental employee behavior. The hierarchical model introduces innovation in the field of GHRM because ISM-based hierarchical models are flexible enough to include or exclude practices according to the green organizational objectives in the hospitality industry within the context of Pakistan. The results offer a comprehensive illustration of the importance of GHRM practices in facilitating, encouraging and promoting employees to take green initiatives and achieve business sustainability. Research limitations/implications The study utilizes the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique to identify key success criteria for GHRM, while the innovative approaches of ISM and MICMAC techniques were used to investigate employee pro-environmental behaviors. This novel method gives GHRM research an analytical direction by providing an organized framework for evaluating the impact of GHRM initiatives on environmental outcomes. Additionally, by focusing on developed economies rather than emerging ones, our study within Pakistan’s hospitality sector fills a knowledge vacuum on the dynamics of GHRM in a developing nation. Practical implications This study highlights the significance of managers in the hospitality sector serving as role models for implementing GHRM practices to encourage pro environmental behavior among employees. Prioritizing green structural capital, establishing standard environmentally friendly criteria for hiring and evaluating prospective employees and initiating green projects to promote a psychologically green environment are some of the key recommendations. Improving environmental performance, employee satisfaction and loyalty in the hotel industry requires constant communication, training and employee participation in sustainability decision-making. Originality/value The GHRM practices have been extensively discussed by academics and researchers. However, there is a notable absence of discussion on the key factors that play a role in transforming employees’ attitudes and behaviors.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».