标题： 关于企业社会责任和绿色供应链的LLM偏差的详细研究 显示英文标题

标题： A Detailed Study on LLM Biases Concerning Corporate Social Responsibility and Green Supply Chains

摘要： 组织越来越多地使用大型语言模型（LLMs）来改进供应链流程并减少环境影响。 然而，已证明LLMs会再现关于可持续商业战略优先级的偏见。 因此，识别LLMs在可持续商业和供应链实践的重要性及作用方面的训练数据偏见至关重要。 本研究调查不同LLMs对有关企业伦理和责任的作用以及与供应商和客户可持续实践和关系重要性的验证问卷的反应。 使用标准化问卷，我们系统分析由最先进的LLMs生成的响应以识别差异。 我们进一步评估这些差异是否因四种组织文化类型而增强，从而评估所识别偏见的实际相关性。 研究结果揭示了模型之间的显著系统性差异，并表明组织文化显著修改LLM的响应。 该研究对可持续发展背景下的LLM辅助决策具有重要意义。 显示英文摘要

摘要： Organizations increasingly use Large Language Models (LLMs) to improve supply chain processes and reduce environmental impacts. However, LLMs have been shown to reproduce biases regarding the prioritization of sustainable business strategies. Thus, it is important to identify underlying training data biases that LLMs pertain regarding the importance and role of sustainable business and supply chain practices. This study investigates how different LLMs respond to validated surveys about the role of ethics and responsibility for businesses, and the importance of sustainable practices and relations with suppliers and customers. Using standardized questionnaires, we systematically analyze responses generated by state-of-the-art LLMs to identify variations. We further evaluate whether differences are augmented by four organizational culture types, thereby evaluating the practical relevance of identified biases. The findings reveal significant systematic differences between models and demonstrate that organizational culture prompts substantially modify LLM responses. The study holds important implications for LLM-assisted decision-making in sustainability contexts.