This paper examines the dynamics of carbon quota pricing and emissions under government subsidies in the EU carbon market. The study reveals three core findings. First, carbon emissions, carbon subsidies, and carbon quota prices exhibit strong interconnectedness with pronounced seasonality, and spillover effects intensify during exogenous shocks, particularly at short-term frequencies within one to five days. Second, Germany consistently serves as the primary source of spillover effects, reflecting its energy-intensive industrial structure and dominant position in the EU Emissions Trading System, while carbon subsidies function as information receivers in the short term but maintain stable roles in the medium to long term under the EU's sustained climate commitments. Third, the COVID-19 pandemic fundamentally altered spillover patterns, with the EU industrial sector transitioning from a net transmitter to a net recipient of spillovers and carbon quota prices shifting to net recipients during the shock. These findings are derived from a stochastic differential game model that captures strategic interactions between governments and enterprises under exogenous shocks, combined with TVP-VAR spillover analysis that quantifies dynamic connectedness across time and frequency domains. The results enhance the understanding of carbon market mechanisms under policy interventions and external disturbances, offering insights for the development of more efficient and resilient carbon trading systems.

Under increasing external uncertainty, promoting sustainable transformation and building data-driven supply chain resilience (SCR) supported by frontier technologies has become an important issue. This study uses Chinese A-share listed companies from 2005 to 2024 as the sample. From the perspective of frontier technologies, it employs text analysis and machine learning to identify large-scale unstructured annual report texts and quantify firm circular economy (CE) practices. SCR is measured using an entropy-weighted indicator system, and the relationship between CE practices and SCR is examined using panel regression models. The results show that CE practices significantly improve SCR, and the findings remain robust across multiple robustness and endogeneity tests. Mechanism analysis indicates that CE practices enhance SCR through three channels: resource effects, structural effects, and collaboration effects. Heterogeneity analysis reveals that the positive effect is more pronounced in non-state-owned firms, firms in non-heavy-polluting industries, high factor-intensive firms, and firms with active environmental information disclosure, as well as in regions with higher economic development and stronger governmental attention to green development, and in the period following the signing of the Paris Agreement in 2015. Further analysis shows that CE practices significantly improve the resistance dimension of SCR, while their effect on recovery is insignificant. Economic consequence analysis indicates that SCR enhancement driven by CE practices helps reduce operational risk and increase firm value. This study provides new empirical evidence on how CE practices strengthen SCR, and offers theoretical and practical implications for enabling sustainable supply chain development through frontier technologies and data-driven analytics.