人工智能能否促进绿色创新?基于直接、间接、溢出和异质性效应的评估

Qiang Wang, Tingting Sun, Rongrong Li
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摘要

本文以可持续发展目标为背景,探讨了人工智能(AI)与绿色创新之间错综复杂的关系。随着社会努力实现可持续发展,了解技术进步与环境进步之间的动态关系变得至关重要。本研究利用 2000 年至 2019 年间 51 个国家的面板数据,采用固定效应模型、中介效应模型和空间杜宾模型,细致研究了人工智能对绿色创新的影响。实证研究结果表明,人工智能与绿色创新之间存在稳健且显著的正相关关系,凸显了人工智能在促进环境创新方面的关键作用。对发达经济体和发展中经济体的异质性分析划分了人工智能对绿色创新影响的差异,揭示了经济发展水平和金融结构的影响。与发展中国家相比,发达国家的人工智能与绿色创新之间的关系更为明显,凸显了在不同经济环境中采用技术的复杂性。此外,本研究还深入探讨了人工智能与绿色创新关系的传导机制,揭示了产业结构和人力资本的中介作用。产业升级和人力资本提升是人工智能间接刺激绿色创新的重要途径。空间分析揭示了绿色创新在全球范围内的空间相关性,强调了人工智能不仅在国内范围内,而且在邻近地区也有重大影响。人工智能对绿色创新有重大的直接、间接和总体影响,凸显了其溢出特性及其在全球范围内推动人工智能合作发展的催化作用。这项研究对人工智能与绿色创新之间的相互作用提出了细致入微的见解,为政策制定者、企业和研究人员理解技术干预在促进可持续创新方面的多面性奠定了基础。研究结果强调,必须通力合作,利用人工智能的潜力推动绿色创新,从而推进全球可持续发展议程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Does artificial intelligence promote green innovation? An assessment based on direct, indirect, spillover, and heterogeneity effects
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 reveals the spatial relevance of green innovation globally, emphasizing AI's substantial impact not only within domestic spheres but also across neighboring regions. There are significant direct, indirect, and total effects of AI on green innovation, highlighting its spillover characteristics and the catalytic role it plays in driving collaborative AI development on a global scale. This research contributes nuanced insights into the interplay between AI and green innovation, providing a foundation for policymakers, businesses, and researchers to comprehend the multifaceted dimensions of technological interventions in fostering sustainable innovation. The findings emphasize the imperative of collaborative efforts in utilizing AI's potential to propel green innovation, thereby advancing global sustainability agendas.
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