基于制度理论和资源依赖理论，选取2011~2022年沪深A股制造业上市公司数据，利用双重差分法考察国家级大数据综合试验区（简称国家大数据试验区）作为非“降碳减排”针对性政策对碳绩效的影响及作用机制。研究发现，国家大数据试验区显著提升了企业碳绩效，这一结论经过一系列稳健性检验后依然成立。机制分析发现，国家大数据试验区能够通过数字驱动、绿色创新、人财保障提升企业碳绩效。异质性分析发现，行业污染越严重、地区环境规制强度越高、高管绿色认知水平越高、政府治理水平越高、媒体关注度以及公众环境关注度越高，国家大数据试验区对企业碳绩效的管理效果越好。

Drawing upon institutional theory and resource dependence theory, this study selects data from A-share listed manufacturing firms in Shanghai and Shenzhen spanning 2011 to 2022. Utilizing a difference-in-differences methodology, it investigates the impact and underlying mechanisms through which the National Big Data Comprehensive Pilot Zone (NBDCPZ)—a policy not explicitly targeted at carbon reduction or emission abatement—affects corporate carbon performance. The findings reveal that the NBDCPZ significantly enhances enterprises’ carbon performance, a conclusion that remains robust after a series of sensitivity analyses. Mechanism analysis indicates that the NBDCPZ improves corporate carbon performance through digital driving, green innovation, and the strengthening of human and financial capital security. Additionally, heterogeneity analysis demonstrates that the facilitating effects of the NBDCPZ on carbon performance are more pronounced in industries with higher pollution levels, regions with stricter environmental regulations, firms led by executives with elevated green awareness, areas characterized by stronger governmental governance, higher media attention, and heightened public environmental concern.