供应链
数字化
经验证据
稳健性(进化)
高效能源利用
数字化转型
背景(考古学)
计算机科学
产业组织
实证研究
人工智能
能源供应
供应链管理
业务
大数据
商业智能
面板数据
能量(信号处理)
机器学习
知识管理
工业4.0
作者
Junxian Liu,Zixuan Yang
标识
DOI:10.1016/j.iref.2026.105517
摘要
In the context of the synergistic development of digitization and green development, exploring whether supply chain digital intelligence can improve corporate energy efficiency is of great importance. In this paper, we employ a double machine learning model to investigate the impact of supply chain digital intelligence on corporate energy efficiency and its potential mechanisms, based on panel data of Chinese A-share listed companies from 2012 to 2023. The findings indicate that the digital and intelligent transformation of supply chains improves corporate energy efficiency, and this conclusion remains robust even after a series of robustness tests. Further, heterogeneity analysis reveals that the efficiency improvement effect of supply chain digital intelligence is more significant under high environmental uncertainty, especially for non-state-owned firms, heavily polluting firms, and firms with higher risk-taking levels. Finally, the mechanism test finds that supply chain digital intelligence improves energy efficiency by enhancing specialization, promoting technological innovation, and reducing supply chain concentration. This paper provides empirical evidence and practical insights for exploring the low-carbon effects of the digital intelligence transformation of supply chains.
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