研究大模型代理的消费行为，构建新型经济理论框架。
LLM Consumer Behavior Theory: Foundations of a Novel Research Field
- 从经济学视角分析大模型代理如何决策
- 揭示代理行为与人类偏好间的映射机制
- 适合关注AI代理、市场机制的研究者
大型语言模型（LLMs）正越来越多地作为自主代理，代表用户做出消费决策。这一转变对传统消费者理论提出了根本性挑战，后者长期以人类为决策主体。本文提出「大模型消费行为理论」，一个专注于智能体市场中消费者行为的新研究领域。基于经典与行为经济学，结合自然语言处理最新进展，论文形式化了人类偏好如何通过基于LLM的代理被反映与执行，并探讨代理级决策如何聚合为市场总需求。该理论统一了此前关于LLM决策、人类行为模拟及偏好获取的零散研究，强调在智能体市场中理性与异质性等假设可能失效。本文不提供实证验证，而是界定该领域的研究范围，提出关于对齐、偏好表征与市场动态等开放问题。
原文摘要 · Abstract (English)
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.
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