Analysis using panel data reveals human-machine collaboration boosts carbon emission performance in cities, suggesting pathways for sustainability.
Grounded in the principles of ecological efficiency, this study prioritizes the minimization of natural resource inputs alongside the maximization of derived value, and constructs a multi-dimensional carbon emission performance index across economic, social, and environmental factors. Utilizing panel data from 300 Chinese cities over the period 2012 to 2022, this research dissects the impact and underlying mechanisms of industrial intelligence on urban carbon emission performance. The findings show: (1) Industrial intelligence substantially enhances urban carbon emission performance, with findings remaining robust across various tests. (2) Moderation analysis indicates that green technological innovations and advancements in human-machine collaboration mechanisms for improving carbon emission performance. (3) Subgroup regressions suggest that the positive impact of industrial intelligence on carbon emission performance is more marked in cities with higher overall emissions and where there is a strategic emphasis on scientific talent by local governments. (4) The beneficial effects of industrial intelligence are more accentuated in non-traditional industrial cities than in established industrial bases, with significantly stronger impacts observed in peripheral cities compared to central urban areas. The study extends the discourse on sustainable development by providing actionable insights into the strategic deployment of industrial intelligence to foster environmental sustainability and improve urban carbon management practices.
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Wu et al. (2025) studied this question.
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