This study employs the establishment of the data managment agency as a quasi-natural experiment to construct a theoretical model illustrating how government data governance drives corporate green innovation. Using panel data from listed enterprises from 2010 to 2024 and applying a uble Machine Learning(DML) approach, we empirically find the results as following: Firstly, government data governance significantly enhances enterprise green innovation efficiency. Secondly, the green innovation promotion effect is more pronounced in highly digitalized enterprises, monopolistic industries, and central cities. Thirdly, government data governance improves green innovation efficiency through supporting digital technology R&D, optimizing digital management organizations, and enhancing the digital ecosystem. This study provides practical strategies for governments to manage data elements effectively and offers a theoretical basis for advancing corporate green transformation.
LU Yang
,
WANG Yu-bao
. Government data governance and corporate green innovation efficiency: Empirical evidence based on double machine learning[J]. Urban Problems, 2025
, 355(2)
: 58
-69
.
DOI: 10.13239/j.bjsshkxy.cswt.250206
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