A Logical Impact on Employee Management and Loyalty in the Modern Workplace Based on HR Sustainability Development Using Machine Learning

An examination of leadership, loyalty, the workplace, training, employee engagement, pay, and organizational justice as they pertain to organizational settings is the focus of this research. We used questionnaire distribution as a main data gathering tool, testing seven hypotheses based on two variables. The efficiency of the proposed scheme is evaluated by cross-validation with the traditional model called Recurrent Neural Network (RNN). This research introduces a novel learning-based technique called Neural Learning based Employee Management (NLEM). By shedding light on the complexities of employee engagement, our study questions commonly held beliefs. These parameters are examined in great detail using the independent-samples Kruskal-Wallis test. We found no statistically significant relationship between the investigated factors and employee engagement levels, which contradicts popular assumption. This calls into question the efficacy of tried-and-true engagement tactics and highlights the necessity for more sophisticated methods. Our study fills a vacuum in the literature and shows how important it is to reevaluate current approaches to employee engagement.