Exploring the Nexus Between Socially Responsible Human Resource Management, Employee Green Behavior, Learning Goal Orientation, and Moral Identity: A Novel Perspective Using BSP-CRF Technique

Abstract

This proposed aimed to understand how green human resource management (GHRM) enhances workers' environmental performance. It focuses on how GHRM practices affect employees' voluntary and task-related green performance behaviors. Gender and individual personal environmental values function as moderators, and organizational identity acts as a mediator. The method primarily entails three stages: preprocessing, feature selection, and model training. Missing data handling and min-max normalization are part of the preprocessing, with min max yielding the best outcome. There are two main categories of agents in feature selection: information selection agents and appreciation providing agents. For the purpose of evaluating pupils' progress, this system builds a BSP-CRF model. This approach seems dated when compared to BSP and CRF. The data clearly shows an improvement, with an incredible accuracy percentage of 96.34%.