Does artificial intelligence promote green innovation? An assessment based on direct, indirect, spillover, and heterogeneity effects

作者：Qiang Wang, Tingting Sun, Rongrong Li · 发表于：Energy & Environment · 年份：2023 · DOI：10.1177/0958305x231220520 · 被引用次数：227 · 研究领域：Energy, Environment, Economic Growth、Environmental Sustainability in Business、Innovation Diffusion and Forecasting

This paper investigates the intricate relationship between artificial intelligence (AI) and green innovation within the context of sustainable development goals. As societies strive to achieve sustainability, understanding the dynamics between technological advancements and environmental progress becomes paramount. Drawing from panel data encompassing 51 countries between 2000 and 2019, this study employs fixed-effects models, mediated effects models, and spatial Durbin models to meticulously examine the influence of AI on green innovation. The empirical findings reveal a robust and significantly positive correlation between AI and green innovation, highlighting the critical role of AI in fostering environmental innovation. Heterogeneity analysis across developed and developing economies delineates variations in the impact of AI on green innovation, shedding light on the influence of economic development levels and financial structures. Developed nations showcase a more pronounced AI-green innovation relationship compared to their developing counterparts, highlighting the complexities of technology adoption within distinct economic landscapes. Moreover, this study delves into the transmission mechanisms underlying the AI-green innovation nexus, revealing the mediating roles of industrial structure and human capital. Industrial upgrading and the enhancement of human capital emerge as crucial pathways through which AI indirectly stimulates green innovation. Spatial analyses rev...