The Impact of Downstream Firms’ New Quality Productive Forces Empowered by Artificial Intelligence on Upstream Firms’ Carbon Emissions: The Mediating Effect of Supply Chain Resilience
Lu Wang, Ziying Zhao, Xiaojun Xu, Xiaoli Wang, Mohammad Adeeb, Ru Yu
Yanshan University Jilin University
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摘要与影响
The advancement of artificial intelligence technology is profoundly reshaping firms’ production models and operational methods. When driven by artificial intelligence, new quality productive forces (NQPF) are exhibiting greater development potential and green efficacy. Utilizing data on Chinese listed firms from 2013 to 2022, this study employs vertical relationship theory to empirically examine the impact of NQPF in downstream firms on carbon emissions in upstream firms, as well as the transmission mechanisms. The empirical findings show that the NQPF of downstream firms significantly curbs the carbon emissions of upstream firms; in other words, a 1% increase in the NQPF index of downstream firms leads to a 0.187% decrease in the carbon emissions of upstream firms. Among the sub-indicators of NQPF, technological productive forces demonstrate the most pronounced effects on emission reduction. Mechanism analysis reveals that the NQPF of downstream firms effectively enhances supply chain resilience by optimizing supply-demand matching, stabilizing supply-demand relationships, and improving supply quality, which collectively incentivize upstream firms to reduce carbon emissions. Furthermore, heterogeneity analysis indicates that this backward spillover effect is more pronounced when the upstream suppliers are state-owned, technology-driven, or labor-intensive. These findings provide valuable empirical insights and policy suggestions for optimizing the development path of NQPF, promoting the establishment of green supply chains, and reducing carbon emissions in firms.
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经济 / 管理Sustainable Supply Chain Management
Energy, Environment, Economic Growth · Impact of AI and Big Data on Business and Society