The Impact of Artificial Intelligence Demonstration Zone Policies on the Green Innovation Resilience of Manufacturing Firms

Using firm-level panel data from Chinese A-share-listed manufacturing firms over the period 2019–2024, this study exploits the staggered implementation of the National New-Generation Artificial Intelligence Innovation and Development Demonstration Zones as a quasi-natural experiment. A multi-period difference-in-differences (DID) framework is employed to identify the causal effect of AI demonstration zone policies on firms’ green innovation resilience, while further investigating the underlying mechanisms and heterogeneous effects. The empirical results indicate that the establishment of AI demonstration zones significantly strengthens the green innovation resilience of manufacturing firms. This finding remains robust to a series of alternative specifications, placebo tests, and other robustness checks. Mechanism analyses suggest that the policy operates through three complementary channels. First, AI-oriented policy support improves firms’ total factor productivity, enhances their capacity to adapt to changing environments, and thereby improves the efficiency and continuity of green technology innovation. Second, fiscal subsidies and tax incentives associated with the policy help ease financing constraints and mitigate the financial risks inherent in green innovation activities. Third, the policy promotes firms’ substantive green innovation, enabling them to accumulate technological capabilities and reserves that strengthen their ability to respond to environmental regulatory pressures and market uncertainty. Further analysis reveals significant heterogeneity across firms. The positive effect is more pronounced among non-state-owned enterprises, firms facing stronger market competition, and high-tech manufacturing firms. Overall, the findings provide micro-level evidence that AI-oriented development policies can generate broader environmental and innovation benefits beyond their direct technological objectives. They also highlight the potential of digital technology policies to strengthen firms’ capacity to sustain green innovation in the face of regulatory, financial, and market uncertainties, offering relevant implications for developing economies pursuing digital transformation and sustainable development.

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Publication Details

Journal
Sustainability
Published
2026-10-04
DOI
https://doi.org/10.3390/su181910141
Primary Topic
Environmental Sustainability in Business
Type
article
Field-Weighted Citation Impact
0.00
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article

The Impact of Artificial Intelligence Demonstration Zone Policies on the Green Innovation Resilience of Manufacturing Firms

Chaobo Zhou, Lixing Liu
Sustainability
Environmental Sustainability in Business
article

The Impact of Artificial Intelligence Demonstration Zone Policies on the Green Innovation Resilience of Manufacturing Firms

Chaobo Zhou, Lixing Liu
article en

Abstract

Using firm-level panel data from Chinese A-share-listed manufacturing firms over the period 2019–2024, this study exploits the staggered implementation of the National New-Generation Artificial Intelligence Innovation and Development Demonstration Zones as a quasi-natural experiment. A multi-period difference-in-differences (DID) framework is employed to identify the causal effect of AI demonstration zone policies on firms’ green innovation resilience, while further investigating the underlying mechanisms and heterogeneous effects. The empirical results indicate that the establishment of AI demonstration zones significantly strengthens the green innovation resilience of manufacturing firms. This finding remains robust to a series of alternative specifications, placebo tests, and other robustness checks. Mechanism analyses suggest that the policy operates through three complementary channels. First, AI-oriented policy support improves firms’ total factor productivity, enhances their capacity to adapt to changing environments, and thereby improves the efficiency and continuity of green technology innovation. Second, fiscal subsidies and tax incentives associated with the policy help ease financing constraints and mitigate the financial risks inherent in green innovation activities. Third, the policy promotes firms’ substantive green innovation, enabling them to accumulate technological capabilities and reserves that strengthen their ability to respond to environmental regulatory pressures and market uncertainty. Further analysis reveals significant heterogeneity across firms. The positive effect is more pronounced among non-state-owned enterprises, firms facing stronger market competition, and high-tech manufacturing firms. Overall, the findings provide micro-level evidence that AI-oriented development policies can generate broader environmental and innovation benefits beyond their direct technological objectives. They also highlight the potential of digital technology policies to strengthen firms’ capacity to sustain green innovation in the face of regulatory, financial, and market uncertainties, offering relevant implications for developing economies pursuing digital transformation and sustainable development.

SustainabilityVol. 18(19)
Wuhan University (CN)
Openalex Percentile: Top 6%
Environmental Sustainability in Business
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