Zhu, Minghao, Liang, Chen, Lee, Peter K. C., Yeung, Andy C. L. and Zhou, Honggeng (2026). Does Digital Technologies Deployment Promote Environmental Performance? Evidence From China. IEEE Transactions on Engineering Management, 73 , pp. 712-725.
Abstract
In the face of escalating environmental challenges and growing regulatory and stakeholder pressures, improving firms’ environmental performance has become an essential strategic objective. Digital technologies (DTs) are increasingly viewed as transformative tools that can support firms in achieving sustainability goals. However, despite growing interest, existing empirical evidence on the impact of DTs deployment on environmental performance remains fragmented and inconclusive. Moreover, limited empirical research has examined how DTs interact with human-centered production systems, such as lean management, to shape environmental outcomes. Addressing these gaps, this study draws on the natural-resource-based view to investigate whether and how DTs deployment enhances firms’ environmental performance, and how this relationship is moderated by lean production and environmental leadership. Using longitudinal data from publicly listed firms in China, our analysis reveals that DTs deployment has a significant positive effect on environmental performance, and this effect is amplified in firms exhibiting higher levels of lean production and environmental leadership. These findings remain robust across various estimation strategies, including alternative variable specifications, instrumental variable methods, Heckman two-step correction, and a quasi-natural experiment. By providing large-scale empirical evidence on the environmental implications of digital transformation and its interaction with lean practices, this study contributes to the emerging literature on Industry 4.0 and sustainable operations, offering actionable insights for managers and policymakers committed to green transition.
| Publication DOI: | https://doi.org/10.1109/TEM.2025.3647213 |
|---|---|
| Divisions: | College of Business and Social Sciences > Aston Business School > Operations & Information Management College of Business and Social Sciences College of Business and Social Sciences > Aston Business School |
| Funding Information: | This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant DUT25RC(3)001 and in part by the National Natural Science Foundation of China under Grant 72572026. |
| Additional Information: | Copyright © 2025, IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Uncontrolled Keywords: | Leadership,Lean production,Sustainable development,Artificial intelligence,Green products,Fourth Industrial Revolution,Technological innovation,Real-time systems,Internet of Things,Instruments |
| Publication ISSN: | 1558-0040 |
| Last Modified: | 07 Jan 2026 18:14 |
| Date Deposited: | 07 Jan 2026 18:14 |
| Full Text Link: | |
| Related URLs: |
https://ieeexpl ... ument/11313553/
(Publisher URL) |
PURE Output Type: | Article |
| Published Date: | 2026-01-01 |
| Published Online Date: | 2025-12-23 |
| Accepted Date: | 2025-12-18 |
| Authors: |
Zhu, Minghao
Liang, Chen Lee, Peter K. C. (
0000-0001-5100-0316)
Yeung, Andy C. L. Zhou, Honggeng |
0000-0001-5100-0316