PREDICTION of WORKER MOTIVATION with ARTIFICIAL NEURAL NETWORKS and LINEAR MODELING

Year 2022, Issue: 051, 330 - 339, 31.12.2022

Akın Erdemir Fatih Seyran Tuğrul Batırer

Abstract

Organizational justice is a motivation tool that can produce positive results for the organization and employees in working life. The decrease in the perception of justice can cause moral disorders of the employees, may lead them to leave the organization and even to engage in negative behaviors towards the organization. This study was carried out to determine the effect of organizational justice perceived by employees on employee motivation and to predict organizational justice and motivation. The research was carried out with 294 participants working in public institutions serving in Isparta. Firstly, multiple regression analysis was conducted to test the effect of organizational justice on employee motivation. Within the scope of the study, linear modeling and artificial neural networks (ANN) models were also compared in order to contribute to the literature. Multiple regression analysis results showed that interactional and distributive justice had a significant and direct effect on motivation. In addition, it was determined that the highest predictive power was ANN (R² = 0.88) according to motivation models. As a result of the study, the predictability of the organizational justice phenomenon perceived by the employees and the motivation of the employee has emerged.

Keywords

Artificial Neural Networks, Employee Motivation, Organizational Justice, Organizational Management

Thanks

The authors declare that there is no conflict of interest. Also, thanks to Emre KUZUGUDENLI and Canpolat KAYA for their model suggestions. This study was presented as a summary paper with the title "The Effect of Organizational Justice on Employee Motivation: An Application with Linear and Artificial Neural Network Models" at the 3rd International Conference on Applied Engineering and Natural Sciences held on 20-23 July 2022

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