Modeling the Nonlinearities Between Coaching Leadership and Turnover Intention by Artificial Neural Networks

Abstract

This present work uses artificial neural networks (ANNs) to examine the association between various dimensions of coaching leadership and turnover Intention. The coaching leadership data were collected from 194 employees across multiple schools in Korea. The ANN models are capable of higher predictive accuracy than conventional linear regression analysis. An individual ANN software was developed to predict and evaluate the relative importance of input variables on turnover intention. Furthermore, we identified the nonlinear relationship by performing a sensitivity analysis on the model. Based on the results, we concluded that coaching leadership strongly affects teachers' attitudes toward not leaving their school. The graphical illustration of results provided strong evidence of nonlinear and complexity, suggesting that ANN models can recognize the relationship between coaching leadership dimensions with turnover Intention.