这篇论文把LLM当作消费决策的代理人来研究，从经济学角度提出了一个全新的理论框架，适合想了解人机交互市场动态的读者。
该论文正式提出LLM消费者行为理论，作为分析LLM代理自主消费决策的新领域。作者结合经典与行为经济学及NLP进展，形式化人类偏好如何通过LLM代理反映并聚合为市场需求。论文梳理了关于LLM决策、人类行为模拟和偏好提取的碎片化文献，指出在代理市场中理性与异质性等传统假设可能失效。文章未提供实证验证，而是勾勒研究范围并识别对齐、偏好表示和市场动态等开放问题。
LLM Consumer Behavior Theory: Foundations of a Novel Research Field
Large language models (LLMs) are increasingly deployed as autonomous agents that make consumption decisions on behalf of users. This shift raises fundamental questions for consumer theory, which has traditionally modeled humans as the primary decision-makers. In this paper, we introduce LLM Consumer Behavior Theory, a new field of study concerned with analyzing consumer behavior in agentic markets. Drawing on classical and behavioral economics alongside recent advances in Natural Language Processing, we formalize how human preferences are reflected and acted upon by LLM-based agents, and how agent-level decisions aggregate into market demand. We unify previously fragmented literature on LLM decision-making, human behavior simulation, and preference elicitation under a common economic lens, highlighting where assumptions, such as rationality and heterogeneity, may fail in agentic markets. Rather than providing empirical validation, this paper outlines the scope of LLM consumer behavior and identifies open research questions related to alignment, preference representation, and market dynamics.