As global climate change progresses and the “dual carbon” strategy advances, market-based carbon emission trading systems are of great theoretical and practical importance for green technology innovation. In this paper, A-share listed advanced manufacturing enterprises in pilot regions from 2010 to 2023 are taken as samples, and a multi-period difference-in-differences (DID) method is employed to probe into the mechanism by which this policy influences green technology innovation in China’s advanced manufacturing enterprises. Empirical analysis reveals that carbon emission trading exerts a remarkable promoting impact on green technology innovation in China’s advanced manufacturing enterprises. The study indicates that the policy’s influence on enterprises is indirect; specifically, government policies encourage enterprises to raise their R&D investment, thus facilitating green technology innovation to some degree. Moreover, carbon emission rights prices play a positive moderating role, which is vital for maintaining the policy’s incentive function in long-term green transition—within a reasonable range, carbon prices can enhance the policy’s promoting effect. In addition, enterprise-specific features like company size and asset-liability ratio have certain effects on enterprises’ green technology innovation behaviors. The research findings will offer a theoretical foundation and practical reference for optimizing China’s carbon market mechanism in advanced manufacturing and advancing the green transformation of China’s advanced manufacturing industry.

Against the dual backdrop of iterative AI advancement and deepening green development imperatives, AI-driven industrial intelligence (INT) has emerged as a pivotal force in driving sustainable economic growth. While the existing literature has explored the correlation between INT and green total factor productivity (GTFP), significant gaps remain in the design of multidimensional variables, analysis of environmental regulation (ER), and capture of dynamic effects. From the perspective of ER, this study utilizes provincial panel data from China (2012–2023) to construct an 11-indicator evaluation system for INT development and employs the EBM super-efficiency model to measure GTFP. Furthermore, a two-way fixed effects model combined with a moderated mediation model is established to systematically elucidate the intrinsic linkage mechanism between INT and GTFP. The key findings are as follows: First, INT has a significant positive impact on GTFP. Second, green innovation and spatio-economic synergy are crucial pathways through which INT empowers GTFP. Third, ER exhibits a substitution effect within both the direct and indirect impacts of INT on GTFP, where intensified ER significantly attenuates INT’s positive impacts. Fourth, the enhancement effect of INT on GTFP remains statistically significant with a one-year lag, and the substitution effect of ER persists. This study provides an in-depth analysis of the mechanisms of INT-driven green economic transformation, offering valuable insights for governments to implement differentiated environmental governance strategies tailored to local conditions.

To achieve dual-carbon goals and advance the sustainable development of the automotive industry, China’s Dual-Credit Policy serves as the core long-term mechanism for the low-carbon transition of the automotive industry. Given the coexistence of fuel vehicles (FVs) and new energy vehicles (NEVs) in China, existing research often overemphasizes production output while neglecting energy consumption control, and focuses predominantly on NEVs at the expense of FV optimization. To address these gaps, this paper treats FV fuel consumption and NEV energy efficiency as core endogenous decision variables. We construct profit-maximizing optimal production decision models for both types of manufacturers under the Dual-Credit Policy. Through mathematical derivation, numerical simulations, and empirical tests using actual industrial parameters, this study verifies the existence and uniqueness of optimal solutions. It clarifies the influence mechanisms of policy and market factors on corporate energy decisions and identifies the rules of strategy dominance. The findings reveal that the optimal fuel consumption decisions of FV manufacturers exhibit distinct piecewise patterns and critical threshold effects. Specifically, credit prices, NEV quotas, and fuel consumption standards determine the dominance of compliant (low-consumption) versus non-compliant (high-consumption) strategies. Furthermore, the policy exerts a significant market-oriented positive incentive on the energy efficiency upgrading of NEV manufacturers, with credit prices, market demand, and R&D costs acting as core constraints. Notably, the transition-guiding effect of the policy has clear effective boundaries, and its efficacy highly depends on the alignment between parameter design and market conditions. This research provides theoretical support for manufacturers to formulate energy-optimized production decisions and offers actionable references for the continuous optimization of the Dual-Credit Policy system and the sustainable low-carbon transformation of China’s automotive sector.