Renewable energy technology innovation (RETI) is a crucial way to improve energy poverty and combat climate change. However, few studies have examined the impact of RETI on industrial green transformation and upgrading (IGTU) from the perspective of spatial spillover and its regional boundary. Based on the theory of green growth and sustainable development, this paper expands the connotation boundary of IGTU and measures the IGTU levels of 30 provinces in China from 2006 to 2020 using an improved entropy weight method. Kernel density estimation and Moran’s I index are adopted to portray temporal and spatial patterns, the spatial Durbin model is employed to examine the influencing mechanism and spatial spillover effects of RETI on IGTU and its regional boundaries, and the differential impact of its spatial effects on time, region, resource endowment, and environmental regulation are explored further. The results show that (1) RETI and IGTU in China are steadily increasing, indicating a decreasing spatial differentiation pattern of “east–west”; (2) RETI significantly promotes local IGTU but inhibits neighboring IGTU, forming a “beggar-thy-neighbor” situation; (3) the spatial spillover effect of RETI on IGTU has significant regional boundaries—the spatial spillover effect significantly negative and persists up to 800 km, but it is significantly positive from 800 to 1400 km and shows a trend of increasing and then decreasing; and (4) the promoting effect of RETI on IGTU gradually increases over time, presenting spatial differences of promotion in the east and inhibition in the west. Furthermore, RETI has a more substantial promoting effect on IGTU in non-resource-based regions and strong environmental regulation regions. The findings for China provide concrete evidence for formulating targeted policies and seeking a path for IGTU for other developing countries.

Enhancing green innovation levels is an important objective of the pilot low-carbon city policy (PLCC) in China, but the spatial and temporal heterogeneity of the PLCC policy’s effect on green innovation is unclear. Based on panel data from 285 Chinese cities during 2005–2020, this paper assesses the impact of PLCC on regional green innovation using the difference-in-difference (DID) method. The empirical results demonstrate that the PLCC can obviously promote urban green innovation. In terms of the temporal dimension, the policy effect of PLCC on regional green innovation shows an inverted “U” shape and peaks in the seventh year after implementation. From the spatial dimension, the PLCC can promote surrounding cities’ green innovation through spatial spillover effects within 200 km, and the spillover effect decreases with increasing distance. Mechanism analysis indicates that the PLCC policy can promote regional green innovation by enhancing regional environmental regulations and alleviating financing constraints. This paper explores the temporal and spatial policy effects of PLCC, which can provide effective paths and policy recommendations for China to achieve its “dual carbon” goals.

Most of the existing literature focuses on how international industrial transfer (IIT) impacts the global value chain (GVC) status of the manufacturing industry from the perspective of narrowly defined FDI but ignores the objective fact that FDI and IIT are not equivalent. Based on theory analysis, we used the TiVA database, the input–output model, and global value chain-related methods to effectively measure the scale of generalized IIT and GVCs of manufacturing sectors in China from 1995 to 2018. On this basis, the relationship between IIT and the GVCs of manufacturing industries and the moderating effect of green technological innovation (GTI) were empirically investigated using industry panel data. The results show that (1) there is a nonlinear inverted U-shaped relationship between IIT and manufacturing GVCs; that is, a larger IIT scale is not better from the perspective of manufacturing GVCs. (2) GTI weakens the inverted U-shaped relationship between IIT and manufacturing GVCs. (3) The heterogeneity analysis found that both medium- and high-technology manufacturing IITs have a nonlinear inverted U-shaped relationship with GVCs, which does not exist in low-technology manufacturing IIT. (4) The benchmark regression results remain robust after replacing the GVC measure, excluding special years and endogeneity treatment and replacing the estimation method robustness test. The research in this paper has implications for optimizing the design of IIT policies to promote the upgrading of manufacturing GVC status.

Corporate alliances have become an important way for firms to share the resources and costs of innovation. However, whether corporate technology alliances can effectively enhance the ambidextrous green innovation (AGI) capabilities of firms is a question that still needs to be answered. Building networks of corporate technology alliances based on joint patent application data from the China National Intellectual Property Administration (CNIPA) for the period of 2015–2019, this study investigated the impact of network centrality and structural hole characteristics on exploitative green innovation (IGI) and exploratory green innovation (RGI) from the perspective of internal and external pressures. The empirical results showed that (1) network centrality and structural holes could promote AGI and that the impact on IGI was greater than that on RGI. However, an examination based on lagged effects found a greater impact on RGI. (2) The impact of alliance networks on AGI was positively moderated by internal and external pressures. (3) There were complementary effects between the internal and external pressures. Our study emphasized that it was important to balance AGI to win short-term and long-term competition.

To better address the inequities and inequalities brought by the monotonous approach to low-carbon development, it is necessary to actively explore inclusive low-carbon development (ILCD) pathways, and low-carbon policy (LCP) synergy plays a crucial role in ILCD. This paper manually collected LCP data from 30 provinces in China from 2010 to 2019 and conducted a study using text analysis to measure LCP subject synergy, LCP tool synergy, and LCP overall synergy. At the same time, an indicator analysis framework of ILCD was constructed to measure the efficiency of ILCD at the provincial level through the super-efficient SBM model. On this basis, the impact of LCP synergy on regional ILCD is explored to reveal its mechanism of action, and heterogeneity is explored. The results show the following: (1) In general, LCP subject synergy, LCP tool synergy and LCP overall synergy all effectively promote regional ILCD. (2) Both LCP subject synergy and LCP tool synergy are indispensable. Policy synergy can positively affect ILCD only when both policy subjects and policy instruments are highly synergistic, while ILCD is significantly weakened when both policy subjects and policy instruments are lowly synergistic. (3) The stronger the innovation capacity of provinces, the stronger the contribution of LCP synergy to ILCD. (4) In non-resource-based regions, the effect of LCP subject synergy on regional ILCD is more significant, and the effect of LCP tool synergy is not significant, while the opposite is true for resource-based regions. The study plays a certain reference significance for the government to improve LCP synergy and promote regional ILCD.