Exploring the TMT Decision-Making Process Using Multi-Agent Systems: A Research Study

Abstract

This research study investigates the decision-making process of Top Management Teams (TMTs) utilizing multi-agent systems (MAS). TMTs play a crucial role in shaping organizational strategies and driving innovation, yet the decision-making dynamics within these teams are complex and often influenced by various internal and external factors. Drawing on principles from artificial intelligence and organizational behavior, we propose a theoretical framework that models TMT decision-making as a multi-agent system, where individual team members represent autonomous agents with unique goals, preferences, and decision-making heuristics. Through computational simulations and empirical analysis, we examine how different configurations of TMTs and interaction patterns among team members affect decision outcomes and organizational performance. Insights derived from this study contribute to a deeper understanding of the intricacies of TMT decision-making processes and offer implications for enhancing decision quality and effectiveness within organizations.