Green financing has been examined in the literature. However, its impact on carbon intensity has not been fully investigated. This research sets out to fill this gap by using the dimensions of green loans, securities, insurance, and investment. In exploring the connections between green financing, nonfossil energy use, and carbon intensity, we utilized data from 2016 to 2020 to run an advanced quantile modeling. We applied the decision-making unit-method of data envelopment analysis for analyses. Our main findings are as follows. Rapid advances in the green finance sector in Organisation for Economic Co-operation and Development countries were coupled with an increase in nonfossil energy usage, resulting in a decline in carbon intensity. When the growth in nonfossil energy consumption was reduced, green investment was put on hold, and the green financing industry would be negatively impacted. The role of green financing and carbon intensity in nonfossil energy use is coupled with strong government policy interventions. Nonetheless, the effects of green finance initiatives often lag. Moreover, these effects are inconsistent. This research suggests new methods to increase the use of nonfossil energy, build a carbon trading market, and increase the consumption of green financing policies post COVID-19.

In traditional manufacturing enterprises, there are common problems of low added value of products, low profit, and poor business performance. As a result, they endeavor to transform themselves into intelligent manufacturing. To help with their transformation, this paper proposes a decision support model for managers to improve the business performance under different configurations of supply chain concentration and staff structure. Through the fuzzy set qualitative comparative analysis, the membership degree is given to the variables, and then the configuration analysis is carried out. We find that, to facilitate intelligent manufacturing, the concentration degree of supply chain or the structure of employee education should be adjusted according to the results from the qualitative comparative analysis of fuzzy sets. Two configuration paths to improve business performance are found. When the supply chain concentration degree is relatively decentralized, manufacturing enterprises should expand the proportion of sales personnel and production personnel. In other words, when the sales personnel and production personnel reach the saturation state, low concentration of suppliers and customers is more conducive to the improvement of business performance. The configuration of high proportion of production personnel and low customer concentration tends to lock enterprises in the lower end of the value chain. Therefore, it is critical for enterprises to improve the education level of employees to transform into intelligent manufacturing and improve their business performance.