<![CDATA[Background: Team productivity is a critical factor in organizational performance and is strongly influenced by individual worker motivation and task characteristics. Objective: This study investigates the impact of incentive-based motivation on team productivity under varying levels of task difficulty using an agent-based modeling (ABM) approach. Methods: The model incorporates three core motivational dimensions—achievement motivation, affiliation motivation, and power motivation—along with individual ability levels to simulate task completion behavior within teams. A total of 20 worker agents were simulated across 27 different motivation profile combinations, with task difficulty values categorized into low, medium, and high levels. Each simulation was repeated 30 times to ensure robustness of the results. Productivity was measured based on task completion time, reflecting the collective contribution of team members. Results: The simulation results indicate that motivation profiles significantly affect team productivity depending on task difficulty. For high task difficulty scenarios, teams composed of agents with high achievement and high power motivation demonstrated the fastest task completion times. In contrast, under low task difficulty conditions, agents with high achievement and high affiliation motivation performed more effectively. Medium task difficulty scenarios showed relatively balanced performance across most motivation profiles, with power motivation still contributing to faster completion times. Conclusion: These findings highlight the importance of aligning incentive-based motivation with task complexity to enhance team productivity. The study also demonstrates the usefulness of agent-based modeling as a tool for analyzing complex team dynamics and providing insights into optimal motivation-task matching strategies in organizational settings.]]>
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