Innovation agglomeration leads to changes in the hierarchical structure of innovation, driving regional economic development. We establish a general equilibrium framework for urban innovation, that is to say, the process of production in a city can be divided into the knowledge production sector and final goods production sector. By this we explain the positive matching relationship between innovation agglomeration and a city’s position in the urban hierarchy (herein called urban tier). Then we empirically analyse 286 prefecture level Chinese cities to evaluate the impact of urban tier on innovation agglomeration using a two-way fixed effect model. To reveal the nonlinear relationship between urban hierarchy and innovation agglomeration, panel quantile and threshold regression models were also used. The main results show that: (1) The spatial structure of innovation in Chinese cities is consistent with the urban tier, and the urban tier plays a significant role in promoting innovation agglomeration. (2) Heterogeneous spatial structures of innovation among urban tiers are reflected in the higher agglomeration of innovation resources in high-tier cities, and the impact of city scale on innovation agglomeration is nonlinear. When the city scale reaches a certain threshold value, its impact on innovation agglomeration is significantly strengthened.

Knowledge has become the most important factor of production with the emergence of the knowledge economy. We use the system GMM estimation method to analyze how cross-national knowledge transfer (CNKT) impacts the total factor productivity (TFP) of China’s 31 provinces and evolution of China’s ability to absorb foreign knowledge. We also examine the possible intermediary effects of foreign direct investment (FDI), outward FDI, import trade, export trade, and direct technology spillovers between CNKT and TFP. We find that: (1) CNKT improves China’s TFP and positively impacts FDI, import trade, export trade, and direct technology spillover; It shows that CNKT not only helps to improve China’s TFP, but also provides innovative knowledge reserve for the absorption of international technology spillovers. (2) The improvement in the domestic infrastructure construction level, R&D capacity, human capital, economic development and openness has obvious absorption effect on CNKT, which is conducive to the absorption and utilisation of international advanced knowledge. (3) FDI, import trade, and direct technology spillover play a partial mediating role between CNKT and TFP, and the intermediary effect of import trade technology spillover is the strongest.

This paper explored the impacts of the changing urban form on the ecological efficiency of administrative areas and urban agglomerations in China under different regional scales using the slack-based measure of efficiency model. It also measured the morphological characteristics of cities across several regions using the Largest Patch Index (LPI), Patch Density (PD), and Fractal Dimension (FD). Using the threshold regression model, the impact mechanism of urban form on ecological efficiency was examined. Results show that the ecological efficiency of the regions show an “N” type change over time. LPI and PD show a significant impact in promoting ecological efficiency while FD inhibits ecological efficiency but is not significant until the regional scale reaches 1,352 km². We conclude that the development of urban agglomeration is more conducive to improving regional ecological efficiency, which will give policymakers some inspiration in developing a regional development strategy.

Latecomer technology imitation and learning is an important driving force to enhance their competitiveness and total factor productivity (TFP). This paper constructs green TFP (GTFP) based on the SBM–Global–Luenberger index, using Chinese provincial panel data from 2003 to 2017. The marginal effects of foreign direct investment (FDI), outward foreign direct investment (OFDI), import and export, and intangible and total international technology spillovers (ITS) on GTFP were assessed. These effects were analysed under the influence of absorption capabilities such as research and development intensity, economic and financial, and openness. A spatial diffusion model based on three diffusion sources in China’s first-tier cities, Beijing, Shanghai, and Guangzhou, was constructed to describe the heterogeneous impacts of ITS on GTFP under the marketisation of diffusion sources. We found: (1) ITS based on exports and OFDI promote economic, imports and FDI are relatively small, independent technological innovation is the dominant source of economic growth. (2) Considering spatial diffusion, the contribution of Beijing’s ITS is relatively weak, and Shanghai’s contribution is stronger. Coastal areas have the largest marginal effect of ITS on GTFP, and ITS do not attenuate as geographic distances increase. (3) The market has a multiplier effect, modifying the relationship between ITS and GTFP.

In this study, data envelopment analysis (DEA) is used to estimate the scientific and technological innovation efficiency and economic efficiency of China’s provinces and cities from 2000 to 2016. Based on these two efficiency measures, a logistic model is used to calculate their symbiosis. The results show that, while the high scientific and technological innovation efficiency are concentrated in the eastern coastal areas, the high economic efficiency spread from the eastern coastal zones to the inland regions. Further, these efficiencies have gradually shifted from independent development to symbiotic development between 2000 and 2007. From 2008 to 2011, the symbiotic point largely spread, emphasising the difference between regions. After 2012, the symbiotic point gathered around 0 again, indicating that external influences greatly influenced the symbiotic patterns in all regions. Finally, we introduce relevant policy recommendations based on the symbiotic condition.