Abstract
Collaboration is essential in integrating resources, data, and information to ensure organizational performance and competitive advantage. Inter-agent collaboration between employees or members from different teams in the organizations is crucial to achieving the goals. The success factor is related to mental processes between interacting agents which are influenced by the conditions of their team. This study aims to analyze inter-agent collaboration based on sharing the same value system influenced by various organizational elements which are considered as variables in this study. Those are communication of organizational strategy, flat and hierarchical team organization structure, ambidextrous leadership of their team leaders, knowledge-intensive environment, and knowledge absorption. Given the complexity of the research, which seeks to examine agent dynamics within processes and their interactions with organizational environment elements, the study has adopted the Agent-based Modeling and Simulation (ABMS) method. ABMS is highly effective for modeling and analyzing the intricate relationships and behaviors of agents, making it well-suited for exploring dynamic systems. As a recognized soft systems approach, ABMS aligns with the study’s objective of understanding complex organizational interactions. The method's strength lies in its ability to translate real-world conditions into computational models that simulate various organizational scenarios and dynamic conditions. To enhance this approach, the researchers developed a framework called DARMA, short for Development of Artificial Representative Designs in Modeling Agent-based and Simulation, which serves as a methodological advancement in the implementation of ABMS. Several findings of this study show that ambidextrous leadership of team leaders and different types of team organization structures affect inter-agent collaboration. Flat team structures produce higher inter-agent collaboration types than hierarchical team structures that produce more simple inter-agent collaboration types.
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