With the gradual retirement of the first batch of new energy vehicles in recent years, determining the optimal recycling mode has become an urgent concern. Considering the closed‐loop supply chain, the government subsidy system, and different market power structures, this paper studies new energy vehicle recycling decisions and supply chain contract coordination. The results show that given an increase in government subsidies, the profit of the dominant agent in the closed‐loop supply chain will be higher than that of the follower, and an increase in wholesale and recovery prices may lead to an increase in sales prices. In addition, the effect of government subsidies on battery recovery is better in cases of vehicle manufacturer dominance than in those of battery manufacturer dominance. Finally, when a battery manufacturer is in the dominant position, a revenue sharing contract can incentivize supply chain coordination; when a vehicle manufacturer is in the dominant position, a two‐part tariff contract can realize coordination in the supply chain.

Environmental pollution and resource scarcity characterize the Yellow River Basin. Studying the factors of high-quality development efficiency (HQDE) and its spatial correlation in the Yellow River Basin is conducive to promoting the maximization of resource allocation in the Yellow River Basin. In this study, Super-EBM and Malmquist index were used to measure HQDE in the Yellow River Basin and explore its influencing factors. The results show that: (1) HQDE is higher in cities in the upper reaches of the Yellow River Basin than in the middle and lower reaches. Compared with the degree of technology utilization, the growth of HQDE mainly depends on technological progress. (2) The spatial correlation of urban HQDE decreases has been weakened annually. The high-efficiency cities in the upper reaches of the basin are obviously concentrated, while the middle and lower reaches of the confluence have both high- and low-efficiency cities located near each other. (3) HQDE has a negative geographical spillover effect. Regression analysis shows that energy consumption, economic development level, factor endowment, public awareness of environmental protection, and enterprise green level can promote the HQDE, while foreign investment utilization, environmental pollution, and education support have negative impacts on urban HQDE.

Innovation is the primary driving force for development, and green innovation efficiency (GIE) plays a key role in regional sustainable development. Moreover, environmental regulations (ERs) are also crucial for innovation and green transformation. Considering the heterogeneity of ERs, we assess the dynamic GIE in the industrial sectors of China. We detect their spatial clustering characteristics, and distinguish the impacts of ERs. Results suggest that there exist significant differences in GIE. Provinces such as Hainan, Guangdong and Zhejiang are ranked high, while Gansu, Inner Mongolia and Ningxia are ranked at the bottom, which shows some spatial dependence. The relationship between the administrative regulation and GIE demonstrates a U-shape, and has not reached a critical point, whereas the relationship between the market-based regulation and GIE possesses an inverted U-shape, which is highly significant. Furthermore, a positive linear relationship exists between the lagged public participation regulation and GIE. This paper also proposes that the economic development level and industrial structure are vital factors in accelerating industrial GIE. These conclusions provide scientific support for formulating regional transformation strategies.

Driven by the global energy transition and the pursuit of “dual carbon” goals, sustainability risks within the coal supply chain have emerged as a central obstacle impeding the low-carbon transformation of high-carbon industries. To address the critical gap in systematic and multidimensional risk assessments for coal supply chains, this study proposes a hybrid framework that integrates the analytic hierarchy process (AHP) with the fuzzy comprehensive evaluation (FCE) method. Utilizing the Delphi method and the coefficient of variation technique, this study develops a risk assessment system encompassing eight primary criteria and forty sub-criteria. These indicators cover economic, operational safety, ecological and environmental, management policy, demand, sustainable supply, information technology, and social risks. An empirical analysis is conducted, using a prominent Chinese coal enterprise as a case study. The findings demonstrate that the overall risk level of the enterprise is “moderate”, with demand risk, information technology risk, and social risk ranking as the top three concerns. This underscores the substantial impact of accelerated energy substitution, digital system vulnerabilities, and stakeholder conflicts on supply chain resilience. Further analysis elucidates the transmission mechanisms of critical risk nodes, including financing constraints, equipment modernization delays, and deficiencies in end-of-pipe governance. Targeted strategies are proposed, such as constructing a diversified financing matrix, developing a blockchain-based data-sharing platform, and establishing a community co-governance mechanism. These measures offer scientific decision-making support for the coal industry’s efforts to balance “ensuring supply” with “reducing carbon emissions”, and provide a replicable risk assessment paradigm for the sustainable transformation of global high-carbon supply chains.