Jul 2026· African and Asian Studies· pp. 1-25· 0 citations· 47 references
Abstract
The rapid advancement of scientific innovation and industrial restructuring has extensively promoted high-quality industrial development. However, whether the digital economy (
DE
) can effectively drive the green transformation (
GT
) of manufacturing remains uncertain. This study examines the influence of
DE
on
GT
in China’s manufacturing sector by developing an impact-effect model (
IEM
) to analyze their relationship. The study examines panel data from thirteen Heilongjiang cities using fixed-effect, quantile regression, and threshold models to assess
DE
impacts on
GT
across manufacturing industries. The results reveal heterogeneous effects: industries with lower levels of green development benefit more from
DE
, while advanced sectors experience reduced marginal gains. Digital technologies significantly aid eco-friendly transformation. The findings emphasize the importance of tailoring digitalization policies to industry-specific stages of green development to maximize
GT
potential. Targeted strategies, particularly for less environmentally friendly industries, are recommended to optimize the transformative role of
DE
in sustainable manufacturing.
As China transitions to a higher development stage, the environmental dividends of smart-digital upgrades are growing more prominent. Boosting green total factor productivity (GTFP) in manufacturing is critical for fostering emerging quality-driven productive forces. Employing provincial data from 30 regions (2013–2023), this research utilizes the super-efficiency SBM, fixed-effects, mediation, and moderation models to investigate both the impact and operative pathways of digital-intelligent transformation on manufacturing GTFP. The empirical evidence suggests that: (1) The positive effect of digital-intelligent transformation on manufacturing greening proves robust across endogeneity corrections and various sensitivity tests. (2) Heterogeneity tests indicate that the promotional effect is more pronounced in eastern provinces and areas with weaker pollution loads. (3) Mechanism analysis identifies a dual-edged pathway: while technological innovation serves as a positive conduit, labor structure optimization unexpectedly acts as a suppression channel, weakening the overall positive impact. (4) Moderating effect analysis demonstrates that factor market development strengthens the positive relationship between digital-intelligent transformation and manufacturing GTFP. (5) Threshold analysis based on environmental regulation intensity indicates that the marginal effect of digital-intelligent transformation gradually declines as environmental regulation becomes more stringent. Overall, the findings suggest that the green effects of digital-intelligent transformation are not automatic but depend on regional industrial structures, factor market conditions, and environmental regulatory intensity. Crucially, this study reveals a potential “green paradox” in China’s manufacturing digitalization process: although digital-intelligent technologies stimulate innovation and labor upgrading, their contribution to emission reduction is partially offset by a misalignment in labor allocation and technological orientation, resulting in a net weakening of the green transformation effect. Therefore, policymakers should promote the coordinated development of digital infrastructure, factor market reform, and environmental regulation, while actively guiding skilled labor toward green innovation activities to accelerate manufacturing green transformation and foster new quality productive forces.
The collaborative transformation of digitalization and greening has become a core trend for modern enterprises to build sustainable development systems. As a typical voluntary environmental regulation in China, green factory certification plays an important role in promoting the integration of digital technology and green production. Based on the unbalanced panel data of Chinese A-share listed companies from 2012 to 2022, this paper adopts a multi-period difference-in-differences model to empirically investigate the impact, internal mechanisms and heterogeneous characteristics of green factory certification on corporate digital-green collaborative transformation. The results show that green factory certification can significantly boost the level of corporate digital-green synergy, with an average policy effect of 2.07%. Mechanism tests confirm that this policy realizes the dual transformation through four core paths: stimulating green technological innovation, raising public environmental awareness, improving corporate environmental, social, and governance (ESG) performance and easing financing constraints. Heterogeneity analysis indicates that the promotion effect varies distinctly across regions, enterprise life cycles, pollution types and executive backgrounds. This study reveals the systemic logic of voluntary environmental regulation enabling digital-green collaborative transformation, and provides empirical support and targeted policy suggestions for enterprises and governments to accelerate the integrated development of digitalization and greening.
The digital economy (DE) is a nascent economic model with the potential to mitigate urban industrial pollution (UIP) while encouraging high-quality economic expansion. This paper utilized panel data from 258 Chinese cities and employed the fixed-effects model, the mechanism test model, panel threshold model, and the spatial Durbin model to undertake an empirical investigation into the DE on UIP emissions. The research outcomes suggest that developing the DE has a positive influence on UIP reduction and that the effect of the DE on UIP reduction varies significantly across regions with different levels of industrial development, digital infrastructure, and environmental regulatory intensity. Further examination shows that the DE can reduce UIP by promoting public environmental concern and green technology innovation. Additionally, when the DE is used as a threshold variable, the DE’s impact on UIP emissions exhibits a nonlinear double-threshold effect, with two key turning points of 0.0921 and 0.5515, which constitute a three-stage model of “weak effect—strong effect—weak effect”. When human resource leve is used as a threshold variable, the impact of the digital economy on reducing urban industrial pollution is gradually increasing and exhibits a nonlinear single threshold effect. Under different geographical and economic distance spatial weight matrices, the DE’s development has a substantial negative spatial spillover effect on UIP emissions. That is, developing the local DE can directly reduce local UIP and significantly suppress UIP in neighboring areas indirectly through information sharing and technology diffusion. The findings of this study provide important management insights for government managers to advance environmental governance and promote green development.
Mingzhao Xiong, Yize Li, Haoyi Qi et al.· Frontiers in Environmental S...· 0 citations
The integration of digital technologies and the real economy has a profound impact on the restructuring of the international division of labor. It is becoming an important driver for enhancing the resilience of global value chains (GVCs). Using panel data for 17 manufacturing subsections in China for 2000-2020, the article exam-ines the impact of digital input resources (DIRs) on the resilience of China’s manufacturing industry within GVCs. The findings show that domestic sources of DIRs have a positive impact on the resilience of the Chinese manufacturing industry. The use of digital technologies and resources that are being developed and applied domestically helps strengthen the position of Chinese enterprises in the international arena. At the same time, external sources of DIRs, such as technology and service imports, produce a deterrent effect, which can nega-tively affect the resilience and competitiveness of local producers. The article concludes that a successful inte-gration of digital resources into the manufacturing industry can become a pivotal factor for achieving sustaina-ble growth and economic development in an era of globalization and rapidly shifting market conditions.
Panpan Wu· Теория и практика общественн...· 0 citations
This article provides an overview analysis of the systemic transformation of China's industrial sector toward green and low-carbon development. The authors examine the scale, mechanisms, and results of the greening of Chinese industry, which over the past two decades has transformed the country from a major polluter into a global leader in green transformation. The article analyzes China's green industrial ecosystem, which includes a number of levels: green factories and industrial parks. Particular attention is paid to the latest initiative to create carbon-neutral factories by 2030 and government support measures for the emerging ecosystem. The paper examines sustainable business models using Sidel and the Ziya Green Industrial Park in Tianjin as an example, as well as models for developing low-carbon value chains. It concludes that the Chinese revolutionary experience represents a scalable and economically feasible model for public-private partnerships in sustainable development, which can be adapted to Russian industry's national specifics when transitioning to sustainable business models and developing low-carbon industrial clusters.
L. G. Abdullina, M. Kuzmin· EKONOMIKA I UPRAVLENIE: PROB...· 0 citations
Against the backdrop of digitalization and green development, the sharing economy (SE) has become an important business model for manufacturing firms to long-term sustainable innovation. Based on resource orchestration theory and institutional theory, this study takes Chinese A-share-listed manufacturing firms from 2012 to 2021 as the research sample, empirically examines the impact of the sharing economy models (SEMs) on corporate sustainable green innovation (SGI), as well as the underlying mechanisms and boundary conditions. The results show that SEMs significantly promotes SGI, and resource allocation efficiency and servitization play partial mediating roles in this relationship. Furthermore, media attention and ESG ratings positively moderate the abovementioned relationship, whereas the perception of economic policy uncertainty has no significant moderating effect. This study expands the research scope of SEMs and green innovation and offers a practical guide for manufacturing firms to promote digital transformation and sustainable green development.
Tao Meng, Dongxuan Li, Yiwen Liu et al.· Journal of Global Informatio...· 0 citations