Researchers have developed a new simulation method using Large Language Models (LLMs) to study cognitive biases in multi-stage supply chains. This approach, grounded in a Hierarchical Reasoning Framework, uses agents like DeepSeek and GPT to simulate varying levels of reasoning sophistication across different tiers. The simulations revealed that agents tend to exhibit self-interested behaviors that worsen systemic inefficiencies, but information sharing can effectively mitigate these negative impacts. This work offers a scalable alternative to traditional behavioral experiments for understanding AI-enabled organizations. AI
IMPACT Provides a novel simulation framework for studying AI agent behavior in complex operational environments.
RANK_REASON This is a research paper detailing a new simulation methodology using LLMs to study cognitive biases in supply chains. [lever_c_demoted from research: ic=1 ai=1.0]
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