Examining the multifaceted nature of organizational justice: An integrated analysis using factor analysis and artificial neural networks

Abstract

The study seeks to explore a composite model of organizational justice through the integration of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and an artificial neural network (ANN). The inquiry consists of three separate phases. At first, the Delphi technique identifies various elements that make up organizational justice. Following this, the dimensions are subjected to EFA to reveal the underlying factorial structure of the concept. In the last phase, the identified factors are validated through Confirmatory Factor Analysis (CFA) and then prioritized using an Artificial Neural Network (ANN) to establish their relative importance. The EFA reveals a novel conceptualization of organizational justice, delineating its four distinct facets: distributive justice, procedural justice, interpersonal justice, and informational justice. This conceptualization is further validated through CFA. The ANN has been used to recognize and prioritize model variables as a triangulation. The study's results highlight procedural justice, informational justice, interpersonal justice, and distributive justice as key factors in the overall ambit of organizational justice. This study has significant implications for scholars and corporate executives, providing insights for training, human development, and policy-making. Furthermore, the model presented offers organizational management a valuable tool to ensure justice for employees and improve efficiency. The present investigation is a notable addition to the field of organizational justice as it incorporates artificial neural networks (ANN) as a research methodology, highlighting the crucial importance of justice in organizational settings.