买方人工智能赋能的环境治理与供应商环境争议：一种组织信息处理与信号视角
Buyer Artificial Intelligence-Enabled Environmental Governance and Supplier Environmental Controversies: An Organizational Information Processing and Signaling
浏览论文内容
中文总结 AI 辅助
本研究基于组织信息处理与信号理论，利用2020-2024年41国2505家供应商面板数据，发现买方AI环境治理暴露可减少供应商次年环境争议，且该效应在AI就绪度和监管质量高的国家更强。
中文摘要 AI 辅助
全球供应链中的环境争议对全球买方构成重大风险。本研究考察海外供应商对买方人工智能（AI）赋能的环境治理的暴露程度是否减少供应商环境争议。借鉴组织信息处理理论和信号理论，我们研究供应商对AI赋能治理的暴露如何影响其环境争议，以及这种效应在何种制度条件下发生变化。通过文本分析衡量买方AI赋能的环境治理，我们分析了2020年至2024年间41个国家中2,505家美国上市公司供应商的面板数据，并采用多维固定效应模型。我们发现，供应商对买方AI赋能环境治理的暴露与次年供应商环境争议呈负相关。这种负相关关系在AI就绪度和监管质量较高的供应商所在国更为显著。本研究为AI赋能的可持续性治理和可持续供应链风险管理研究做出贡献。
英文摘要
Environmental controversies in global supply chains pose significant risks for global buyers. This study examines whether overseas suppliers' exposure to buyers' artificial intelligence (AI)-enabled environmental governance reduces supplier environmental controversies. Drawing on organizational information processing theory and signaling theory, we investigate how suppliers' exposure to AI-enabled governance influences their environmental controversies and the institutional contingencies under which this effect varies. Using text analysis to measure buyer AI-enabled environmental governance, we analyze panel data on 2,505 suppliers of U.S.-listed firms across 41 countries from 2020 to 2024 with multidimensional fixed-effects models. We find that suppliers' exposure to buyer AI-enabled environmental governance is negatively associated with supplier environmental controversies in the following year. This negative relationship is stronger in supplier countries with higher AI readiness and regulatory quality. The study contributes to research on AI-enabled sustainability governance and sustainable supply chain risk management.
