In the context of Sustainable Development Goals (SDGs), the transmission of climate risk within supply chains has attracted widespread attention. For companies, there remains a research gap regarding how to leverage AI tools to reshape supply chain resilience and reduce climate reputation risk.
This paper uses a sample of Chinese public listed companies from 2013 to 2023 and innovatively employs machine learning methods to measure corporate climate reputation risk based on over 10 million media news articles. Utilizing a difference-in-differences (DID) model, we examine the impact of smart supply chains on corporate climate reputation risk through the lens of empowerment theory.
The study finds that smart supply chains can enhance green integration within the supply chain and promote green practices among companies, thereby reducing climate reputation risk. Heterogeneity tests indicate that this effect is more pronounced for upstream companies in the supply chain, firms with close customer-supplier relationships, and those located in regions with a stronger public awareness of ESG issues. Moderating effect tests reveal that managerial myopia weakens the role of smart supply chains in mitigating corporate climate reputation risk, while the strength of climate policies enhances this effect.
This research provides valuable insights for companies participating in climate governance and promoting the achievement of carbon neutrality and SDGs from the perspective of smart supply chains and media reputation.
