Digital Transformation, New Quality Productive Forces, and Corporate Environmental Investment: Empirical Evidence from Chinese A-Share Listed Companies

Amplifying corporate environmental investments is a pivotal strategy for achieving the “carbon peak and carbon neutral” objectives of China’s green development initiative. The digital transformation has the potential to generate new quality productive forces by leveraging data, thereby promoting green technology innovation, enhancing technology efficiency, and leveraging the impact of resource reallocation. Consequently, this transition enables enterprises to transition from a “passive compliance” model to a “proactive enhancement” model, thereby achieving a significant quality leap forward in their environmental investment. The present study utilises a sample of Chinese A-share companies from 2011 to 2023 to innovatively construct a multifaceted data model to quantitatively analyse the impact of digital transformation on corporate environmental investment. This analysis incorporates the intermediary effects of enhanced new quality productive forces, the intermediary effects of data application, and the threshold effects of environmental uncertainty, as well as the non-linear effects of industry, property rights, regional differences, policy, and the intensity of production factors. The study’s findings are as follows: (1) Digital transformation significantly promotes corporate environmental investment, and this conclusion is robust. (2) The new quality productive forces have a positive intermediary effect on corporate environmental investment during digital transformation. (3) The application of big data has been demonstrated to moderate the intermediary effects of “digital transformation-new quality productive forces-enterprise environmental investment.” (4) The impact of environmental uncertainty on corporate environmental investment during the digital transformation process is characterised by a “barrier effect,” exhibiting a “border effect” that is non-linear in nature. (5) In the context of the lightweight pollution industry, non-state-owned enterprises, the eastern region, and the implementation of environmental policies, the efficacy of digital transformation in enhancing corporate environmental investment is particularly pronounced. In light of the aforementioned, the present study puts forth four specific recommendations, offering invaluable insights for the contemporary Chinese enterprise to navigate the process of transformation and achieve sustainable, high-quality growth.

Authors

Institutions

Publication Details

Journal
Economies
Published
2025-08-15
DOI
https://doi.org/10.3390/economies13080236
Citations
1
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
3.13

Funders

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

Digital Transformation, New Quality Productive Forces, and Corporate Environmental Investment: Empirical Evidence from Chinese A-Share Listed Companies

Yunsong Xu, Qian Ao
1 citations
Economies
Energy, Environment, Economic Growth
3.13
article

Digital Transformation, New Quality Productive Forces, and Corporate Environmental Investment: Empirical Evidence from Chinese A-Share Listed Companies

Yunsong Xu, Qian Ao
article en
1 citations

Abstract

Amplifying corporate environmental investments is a pivotal strategy for achieving the “carbon peak and carbon neutral” objectives of China’s green development initiative. The digital transformation has the potential to generate new quality productive forces by leveraging data, thereby promoting green technology innovation, enhancing technology efficiency, and leveraging the impact of resource reallocation. Consequently, this transition enables enterprises to transition from a “passive compliance” model to a “proactive enhancement” model, thereby achieving a significant quality leap forward in their environmental investment. The present study utilises a sample of Chinese A-share companies from 2011 to 2023 to innovatively construct a multifaceted data model to quantitatively analyse the impact of digital transformation on corporate environmental investment. This analysis incorporates the intermediary effects of enhanced new quality productive forces, the intermediary effects of data application, and the threshold effects of environmental uncertainty, as well as the non-linear effects of industry, property rights, regional differences, policy, and the intensity of production factors. The study’s findings are as follows: (1) Digital transformation significantly promotes corporate environmental investment, and this conclusion is robust. (2) The new quality productive forces have a positive intermediary effect on corporate environmental investment during digital transformation. (3) The application of big data has been demonstrated to moderate the intermediary effects of “digital transformation-new quality productive forces-enterprise environmental investment.” (4) The impact of environmental uncertainty on corporate environmental investment during the digital transformation process is characterised by a “barrier effect,” exhibiting a “border effect” that is non-linear in nature. (5) In the context of the lightweight pollution industry, non-state-owned enterprises, the eastern region, and the implementation of environmental policies, the efficacy of digital transformation in enhancing corporate environmental investment is particularly pronounced. In light of the aforementioned, the present study puts forth four specific recommendations, offering invaluable insights for the contemporary Chinese enterprise to navigate the process of transformation and achieve sustainable, high-quality growth.

EconomiesVol. 13(8)
Beijing Language and Culture University (CN)
Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 7%
Energy, Environment, Economic Growth
3.13
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.