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Does AI-driven innovation improve green productivity? The role of heterogeneous information infrastructure
1School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Fujian, 361005, China.
Abstract:
Artificial intelligence (AI) 's rapid advancement presents opportunities and challenges for achieving sustainable development goals. In particular, understanding how AI can enhance green productivity is crucial for promoting high-quality, low-carbon economic growth. Nevertheless, few studies have explored the influence of AI-driven innovation on green productivity from the perspective of technological progress. Grounded in endogenous growth theory and the Technology-Organization-Environment framework, this study investigated the relationship between AI-driven innovation and green total factor productivity (GTFP) and examined the moderating role of information infrastructure, using data from 284 Chinese cities between 2011 and 2022. Our results show that AI-driven innovation improves GTFP by improving energy efficiency, human capital, and green innovation. In addition, AI-driven innovation significantly improves GTFP in non-resource-based, environmentally focused, and non-old industrial base cities, but shows no significant impact in resource-based, non-environmentally focused, and old industrial base cities. Finally, information infrastructure amplifies the positive impact of AI-driven innovation, with a threshold effect observed-when information infrastructure reaches a certain level, the benefits of AI-driven innovation on GTFP become more pronounced. Among different types of information infrastructure, both network infrastructure and computing power infrastructure exhibit significant facilitative effects, with the latter showing a stronger influence.
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