Tingting Han

This study investigates the nuanced relationship between green technological innovation (GTI) and urban carbon emissions, addressing the persistent ambiguity in the literature regarding GTI's decarbonisation efficacy. Utilising panel data from 247 Chinese prefecture‐level cities (2006–2020), we employ a spatial Durbin model (SDM) to simultaneously estimate local and spillover effects of GTI while evaluating heterogeneous impacts across non‐pilot cities, innovation pilot cities, low‐carbon pilot cities and dual‐pilot cities (joint innovation‐low‐carbon pilots). Three key findings emerge. First, GTI exhibits an inverted U‐shaped relationship with carbon intensity, where initial innovation accumulation exacerbates emissions before triggering net reductions. Spatial spillovers amplify this effect. Second, emission reductions are contingent on threshold conditions: a minimum GTI output and economic development level. Third, policy design critically mediates outcomes: innovation‐focused pilots local emission reductions and stronger spillovers than low‐carbon pilots, while dual‐pilot cities—through synergistic integration of innovation incentives and carbon pricing—outperform non‐pilots. These results establish that institutional frameworks prioritising innovation‐led policy hybridisation, coupled with inter‐city knowledge diffusion, constitute vital mechanisms for unlocking GTI's decarbonisation potential. The analysis provides actionable insights for designing spatially coordinated, phase‐sensitive urban climate policies.

Utilizing an advanced machine learning algorithm, particularly the Artificial Neural Network (ANN) framework, this study reveals a significant nonlinear and even cyclical relationship between public concern about environmental issues and the ESG performance of Chinese A-share listed companies, covering the period from 2004 to 2020. The findings highlight the effectiveness of the Self-Organizing Map (SOM)-ANN framework in elucidating the empirical relationship between these variables. We contend that robust public monitoring can enhance companies’ ESG initiatives, and we recommend that policymakers implement a series of measures to safeguard and promote public involvement in decision-making processes. Furthermore, our analysis of the combined effects of public concern and various performance metrics on firms’ ESG outcomes indicates that the diversity among firms is crucial for determining the most appropriate level of public participation in their sustainable development efforts. Therefore, managers and policymakers should focus on firm-specific attributes instead of adopting a “one-size-fits-all” approach to maximize the benefits of public engagement.