The aim of this paper was to provide a better understanding of the adoption of GHRM mechanisms to improve employee retention in Nigerian hotels. Specifically, to help managers improve employee retention, as this topic has largely been neglected by researchers studying management in the hotel sector in Nigeria. Therefore, the present study assesses HRM strategies based on responses to 430 structured questionnaires. Data were coded in SPSS23 and analysed using PLS-SEM 3.0. The results show that green personal values (GPV), green recruitment and selection, green training and development, and employee empowerment have positive and significant effects on employee retention. Also, employee empowerment mediates the effects of all other aforementioned variables, except GTD, on employee retention. A notable contribution of this study is the introduction of GPV as an imperative variable that can enhance employee retention in the hotel sector. Managers are encouraged to apply the green HRM strategies discussed in this study, which can be achieved through productive organisational and national human resource development programs. This study emphasises the importance of giving clear and helpful information to organisations to promote sustainable practices in hotels. As such, green human resource management (GHRM) strategies have recently attracted considerable attention from academics and practitioners worldwide as potential methods for enhancing employee commitment.

A single numerical model as integrator of initial value problems of multi-order (1st, 2nd and 3rd) ordinary differential equations is introduced. Utilizing Chebyshev polynomials as the trial function, the method is formulated firstly, by obtaining the continuous form of the proposed scheme via collocation technique and later, arrange in a block-by-block manner as numerical integrator of multi-order ODEs. The convergence properties are investigated and it's established that the proposed method is convergent. A comparison of the problems solved with the new method and existing methods shows that the new method outperformed better than existing methods in terms of accuracy.