Environmental regulation and green innovation are two main fulcrums in the realization of green transition of industrial growth. However, few studies have done an empirical analysis of the impact of environmental regulation and green innovation on green development. Based on the theory of systematic interduality, regional industrial green development is regarded as a dynamic system composed of two subsystems: the state and the process subsystem. Using provincial industrial panel data from 2007–2015 and the spatial Durbin model under the unified analysis framework, this paper examines the role and mechanism of environmental regulation (divided into administrative environmental regulation, market-based environmental regulation, and public participation environmental regulation) in the impact of green innovation (divided into green product innovation and green craft innovation) on industrial green development. The results indicate a sharp fluctuating trend in China’s overall industrial green development performance, and that China’s 30 provinces can be divided into four categories, based on the development levels of two subsystems of industrial green development. There is a clear positive spatial correlation between the industrial green development performance in different provinces. Considering the impact of environmental regulation on industrial green development performance, different types of environmental regulation have different regional influences. Considering the impact of green innovation on industrial green development performance, in the absence of environmental regulation constraints, green product innovation shows a certain promotional role, and green craft innovation has a significant inhibitory effect. However, under environmental regulation constraints, market-based environmental regulation through the encouragement of green craft innovation rather than green product innovation achieves a positive impact on industrial green development.

The industrial revolution has brought a leap in productivity; however, some severe ecological environment and resource problems are coming out with the development of industrialization. To achieve sustainable development of social economy, green technology innovation emerges in response to the proper time and conditions. In this context, the correct approach to measure the efficiency of green technology innovation in China’s industrial enterprises is an important research topic. Based on existing studies, this paper divides innovation activities into two stages based on the innovation value chain and constructs a two-stage evaluation index system including all kinds of undesirable outputs transferred from negative externalities of the ecological environment. To evaluate green technology innovation efficiency, SBM and EBM network DEA models are applied to conduct empirical analysis from the perspective of time and space. This paper also calculates the efficiency values based on the SBM model and the EBM model, respectively, and compares the differences between them. The results show that the efficiency value of the achievement transformation stage is significantly higher than that of technology development stage; there are noticeable gaps in the efficiency of green technology innovation between different regions of China. Besides, the eastern region has a better performance in green technology innovation than the western region and Qinghai has the best green technology innovation performance. Combining the empirical results, the corresponding policy recommendations are put forward.

The impact of social network position on innovation has been widely confirmed in past studies. However, research on the time-lag structure of the impact is still insufficient. Within the time window 2010 to 2017, this study constructs a two-mode social network between Chinese listed companies and other participants. To analyze the lag structure of the effect of social network position on innovation, this study uses a panel negative binomial regression model transformed by the Almon polynomial. The results show that a firm does need an advantageous past social network position for innovation. Previous local and global centrality in a social network has a different influence on innovation. For the local centrality indices, degree centrality has a positive impact in the short-term, but has a negative impact in the long-term; the impact of betweenness centrality is not significant in the short-term and is negative in the long run. For the global centrality indices, closeness centrality has a positive influence that decreases with the increase of the time-lag. At the same time, using the method of necessary condition analysis (NCA), this study calculates the bottleneck for a given innovation level. Finally, based on these research conclusions, the theoretical implications and management practice implications are summarized.

Considering time lag and accumulation of inputs and outputs, this paper adopts the superefficiency data envelopment analysis (DEA) model to study the technological innovation efficiency of high patent-intensive industries using panel data from 2007 to 2017. Given the characteristics and the actual circumstances of the industries, the innovation process is divided into two stages, and an input-output indicator system is established. The results show that the overall innovation efficiency level of high patent-intensive industries in China is increasing. However, the R&D achievements in technology are not quickly applied or sufficiently transformed.

This paper investigates whether the COVID-19 (coronavirus disease 2019) pandemic affects the green inventions of firms, universities, and firm–university collaborations (FUCs) differently. Our identification used provincial-level monthly data from China. Results from the difference-in-differences (DID) model showed that the COVID-19 pandemic has prompted the output of three types of green invention patents. After the parallel-trend test, placebo test, and triple-difference estimation, our conclusion has good robustness. However, the COVID-19 pandemic also influences the role of other policies, such as the SO₂-emissions-trading pilot policy for universities’ green inventions. There has been a slight change in the effect of dual carbon targets on green inventions since the start of the pandemic. The positive effect of the COVID-19 pandemic has been weaker for provinces where the pandemic has been more severe than in other provinces. The results of this study are compared with the results and empirical evidence of other related studies and the theoretical logic of COVID-19 crisis-promoted green inventions are discussed.