SHARED DECISION MAKING AND AI ROLE IN NON-FINANCIAL PERFORMANCE: EXPLORING MODERATING ROLE OF TOP MANAGEMENT SUPPORT AND SECURITY

Abstract

This research investigates the effect of shared decision-making on non-financial performance, with specific attention to the mediating effect of using AI and the moderation effects of security and privacy concerns and top management support. In light of the growing use of AI in decision-making, this study offers important insights into how managerial-level staff view and utilize AI for better organizational performance. A quantitative method was used, with Structural Equation Modeling (SEM) applied in ADANCO to examine data from 245 managerial staff (assistant managers, deputy managers, and corresponding administrative posts). Validated measurement scales of previous studies were utilized, and reliability and validity were guaranteed by thorough statistical checks. Findings validate that shared decision-making largely improves non-financial performance and that AI facilitates this positively. Security and privacy concerns, though, moderate the AI-performance nexus, suggesting data protection issues have the potential to affect AI success. Top management support also bolsters the connection between shared decision-making and performance, emphasizing leadership's pivotal function. The research contributes to decision-making, AI adoption, and organizational leadership research by merging the human, technological, and managerial elements into an integrated model, providing theoretical and empirical understandings for organizations that aim to achieve sustainable competitive advantage.