How digital technologies enhance firm-level energy efficiency in global climate governance

Enhancing energy efficiency is central to global climate governance, yet the role of digital technologies in this process is not fully understood. This study investigates the effects of artificial intelligence, blockchain, cloud computing, and big data on firm-level energy efficiency. Drawing on panel data from 2003 Chinese A-share listed companies between 2013 and 2021, we employ the method of moments quantile regression to capture heterogeneous impacts across efficiency levels. The findings show that digital technologies significantly improve energy efficiency across all quantiles (10th–90th), with the most substantial improvements occurring among the least efficient firms (10th quantile). An energy rebound effect is also observed. Moreover, a composite index of digital technologies consistently outperforms individual technologies in promoting efficiency gains. These results highlight the potential of digital innovation to enhance corporate sustainability and provide policy guidance for advancing the global energy transition.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-07-27
DOI
https://doi.org/10.1057/s41599-026-08514-z
Primary Topic
Sustainable Finance and Green Bonds
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How digital technologies enhance firm-level energy efficiency in global climate governance

Jin Yang, Lingli Qing, Shunhao Mai, Shuaishuai Jia et al.
Humanities and Social Sciences Communications
Sustainable Finance and Green Bonds
article

How digital technologies enhance firm-level energy efficiency in global climate governance

Jin Yang, Lingli Qing, Shunhao Mai, Shuaishuai Jia, Farhad Taghizadeh-Hesary
article en

Abstract

Enhancing energy efficiency is central to global climate governance, yet the role of digital technologies in this process is not fully understood. This study investigates the effects of artificial intelligence, blockchain, cloud computing, and big data on firm-level energy efficiency. Drawing on panel data from 2003 Chinese A-share listed companies between 2013 and 2021, we employ the method of moments quantile regression to capture heterogeneous impacts across efficiency levels. The findings show that digital technologies significantly improve energy efficiency across all quantiles (10th–90th), with the most substantial improvements occurring among the least efficient firms (10th quantile). An energy rebound effect is also observed. Moreover, a composite index of digital technologies consistently outperforms individual technologies in promoting efficiency gains. These results highlight the potential of digital innovation to enhance corporate sustainability and provide policy guidance for advancing the global energy transition.

Humanities and Social Sciences Communications
Tokai University (JP), UCL Australia (AU), Guangzhou University (CN), Guangdong University of Finance (CN), Guangzhou College of Commerce, The University of Adelaide (AU)
Tokai University
Climate action
Openalex Percentile: Top 6%
Sustainable Finance and Green Bonds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

How digital technologies enhance firm-level energy efficiency in global climate governance — Jin Yang, Lingli Qing, et al. · Humanities and Social Sciences Communications (2026) | TGRS Research Map | TGRS