讲话、行走与市场反应：多模态测量AI洗绿及其资本市场后果在中国
Talk, Walk, and Market Response: Multimodal Measurement of AI Washing and Its Capital Market Consequences in China
AI总结：
本文通过多模态方法测量中国AI洗绿现象，发现其对资本市场的负面影响，揭示了AI投资与实际创新之间的关系及市场反应机制。
摘要：
随着人工智能和生成式大语言模型推动产业升级，资本市场日益关注AI主题的上市公司。信息不对称和技术模糊性降低了夸大AI能力相对于真实研发的成本，推动了广泛的AI洗绿。本文利用中国A股市场2018Q1至2025Q2的数据，构建了基于Qwen-VL的AI洗绿风险评分（AWRS）和基于专利质量、AI无形资产资本化和技术人员薪酬的材料真实投资匹配指数（MRMI）。研究发现：（1）AWRS对MRMI的预测能力有限，财务受限企业存在更大的言辞-行动差距；（2）实质性AI投资促进高质量专利，而空洞言辞挤占行业创新；（3）长期机构投资者通过实地考察发现AI洗绿并减少持股；（4）此类抛售引发分析师下调评级、散户抛售及180天内显著估值修正。结果在IV-2SLS和分阶段DID检验中稳健。本研究增强了信息披露和定价效率研究，并支持RegTech以遏制主题投机。
英文摘要：
As artificial intelligence and generative large language models drive industrial upgrading, capital markets increasingly focus on AI-themed listed firms. Information asymmetry and technological opacity lower the cost of exaggerating AI capabilities relative to genuine R&D, spurring widespread AI Washing. Using China's A-share market from 2018Q1 to 2025Q2, we advance literature in measurement and mechanism testing. We construct a multimodal AI Washing Risk Score (AWRS) via Qwen-VL to assess text-image consistency in annual reports and roadshows, and a Material Real-Investment Matching Index (MRMI) from patent quality, AI intangible asset capitalization, and technical personnel compensation using PCA. Four findings emerge: (1) AWRS lacks predictive power for future MRMI, with a wider rhetoric-action gap among financially constrained firms; (2) substantive AI investment boosts high-quality patents, while empty rhetoric crowds out industry innovation; (3) long-horizon institutional investors detect AI Washing through site visits and reduce holdings; (4) such divestment triggers analyst downgrades, retail selling, and sharp valuation corrections within 180 days. Results are robust to IV-2SLS and staggered DID using the ChatGPT shock. This study enhances disclosure and pricing-efficiency research and supports RegTech for curbing thematic speculation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
