数字赋能对传统能源产业低碳转型的影响机制

The Impact Mechanism of Digital Empowerment on Low-carbon Transformation of Traditional Energy Industries

尝试在一个统一的逻辑框架下分析数字赋能传统能源产业低碳转型的影响机制。以2011至2021年中国30个省份的有关面板数据为研究样本,通过熵权-TOPSIS法对数据进行处理,评价区域数字赋能水平与传统能源产业低碳转型的效果;并将样本划分为东中西三大区域,构建动态面板模型,采用系统高斯混合模型(GMM)进行实证分析,进一步探讨数字赋能对传统能源产业低碳转型的影响。结果显示:数字赋能对传统能源产业低碳转型的影响呈现倒“U”型曲线关系;数字赋能水平较高的省份往往传统能源产业低碳转型效果也较好;数字人才有利于传统能源产业低碳转型,能够为产业转型创造价值;不同省份之间数字赋能水平和传统能源产业低碳转型存在较大差异,与区域地理位置、资源分布、政府政策等存在着很大关系。

Trying to analyze the influence mechanism of low-carbon transformation of traditional energy industry under a unified logical framework.This paper takes the relevant panel data of 30 provinces in China from 2011 to 2021 as the research sample,and processes the data through the entropy right-TOPSIS method to evaluate the regional digital empowerment level and the effect of the low-carbon transformation of the traditional energy industry.In addition,the sample is divided into three regions,and the dynamic panel model is constructed,and the systematic Gaussian hybrid model(GMM)method is used for empirical analysis to further explore the impact of digital empowerment on the low-carbon transformation of the traditional energy industry.The results show that the impact of digital empowerment on the low-carbon transformation of the traditional energy industry presents an inverted U-shaped curve relationship;provinces with higher levels of digital empowerment often have better low-carbon transformation effects in traditional energy industries;digital talents are conducive to the low-carbon transformation of the traditional energy industry,and can create value for industrial transformation;there are significant differences in the level of digital empowerment and low-carbon transformation of traditional energy industries among different provinces,which are closely related to their geographical location,resource distribution,and government policies.