Can big data aggregation help businesses save energy and reduce emissions? Quasi-natural experiment in big data comprehensive test

Jingyao Lv, Zhongxiu Zhao and Yongsheng Ji

Structural Change and Economic Dynamics, 2025, vol. 72, issue C, 89-102

Abstract: Aggregating big data pieces is critical for increasing enterprise resource allocation efficiency, reducing energy usage, and lowering carbon emissions intensity. This research aims to investigate the impact of big data aggregation on energy efficiency and carbon emission intensity among Chinese enterprises. To this end, it employs primary financial data from Chinese listed companies from 2009 to 2021 and carbon emissions data disclosed in social responsibility reports, sustainable development reports, and environmental reports. The findings revealed that the aggregation of big data elements dramatically reduces the intensity of carbon emissions in firms in the pilot regions. The decrease effect is more effective in economically developed places and regions with higher degrees of digitization, particularly for organizations in high-energy-consuming industries, and it is more robust for small and non-state-owned businesses. The aggregation of big data elements mainly aids firms in pilot regions in lowering energy consumption and emissions by increasing technical innovation and energy usage efficiency. To create a new national competitive advantage, we should actively promote the gradual expansion of the comprehensive pilot zone for big data, advance the in-depth application of big data in environmental governance, and better capitalize on the dividends of big data aggregation.

Keywords: Big data comprehensive pilot zone; Big data elements clustering; Carbon emissions (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:streco:v:72:y:2025:i:c:p:89-102

DOI: 10.1016/j.strueco.2024.12.003

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