Mediated by AI-Based Generative Re-Enforcement Learning and Work Attitude

Abstract

The primary goal of the chapter was to examine how, in the Ethiopian environment, an employee's work attitude and AI-based reinforcement learning function as mediators between their psychological intrinsic reward system and the perception of organisational support they receive from their employer. Based on their contribution to the GDP of the economy, the textile industries operating in Ethiopia's industrial parks were chosen as the study area. A quantitative research technique and explanatory research design were employed. A multi-phase sampling method was suggested. To assess discriminant and convergent validity, exploratory confirmatory analysis was carried out using AMOS software. It was discovered that the relationship between an employee's psychological intrinsic reward system and the organization's perceived organisational support was extremely poor in the absence of AI-based re-enforcement learning and the employee's work attitude as a mediator. Thus, the work attitude of employees and artificial intelligence (AI) function as a complete mediator.