Green innovation in manufacturing enterprises is crucial for achieving sustainable development, and supply chain digitalization represents a significant avenue to promote such innovation. This research utilizes China’s pilot policy on supply chain innovation and application in 2018 as a quasinatural experiment, analyzing data from listed A-share manufacturing enterprises in China between 2013 and 2022. By employing the Difference-in-Differences (DID) method, we empirically investigate how supply chain digitalization impacts green innovation among Chinese manufacturing enterprises while also exploring potential mechanisms and variations. Our findings reveal that supply chain digitalization significantly improves the efficiency of green innovation within manufacturing enterprises located in pilot cities. Additionally, it influences enterprise green innovation by enhancing their digitization level, reducing reliance on specific customers, and increasing investment in R&D activities. Notably, the impact of supply chain digitalization on green innovation is more pronounced for stateowned enterprises, those situated in western regions, and those with lower levels of regional market integration. Overall, when harnessing the potential benefits of supply chain digitalization for promoting green innovation, attention should be given to critical points as well as regional characteristics.

In order to accelerate the high-quality development of green and low-carbon economy, it is necessary to study the coordination between the regional low-carbon economy and the energy structure. Taking Anhui Province, a resource-based province, as an example, a comprehensive evaluation index system for the coupling of low-carbon economy and energy structure is constructed based on the SDI conceptual framework. Using the entropy weight method for weighting and calculating the development index from 2014 to 2021 to measure the level of regional development, and then using the coupling coordination model to calculate the coupling degree to measure the level of regional coupling. According to the coupling grade, it is divided into different coupling regions (disharmonic, adaptive, and benign). Furthermore, three types of GM (1,1) (traditional, new information, and metabolic) were used to predict the regional coupling level from 2022 to 2026. Finally, a resistance model was used to diagnose resistance in the region. The results show that: (1) The overall development level of energy structure shows a downward trend, while the overall development level of low-carbon economy shows an upward trend. (2) The coupling development of low-carbon economy and energy structure in Anhui Province is on the rise steadily. There is a trend towards primary coordination at the coupling grade, which is developing into a benign coupling region. (3) The overall resistance in the dimension of energy structure shows a steady growth trend, while the overall resistance in the dimension of low-carbon economy shows a steady downward trend.