Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography

Abstract

Sustainable development has become a global consensus, and green innovation is the key starting point, and it has become a ballast stone and stabilizer for regional ecological environmental protection and high-quality economic development. Based on GIS tools and multi-method models, this paper studies the spatio-temporal characteristics and influence mechanism of green innovation in three major urban agglomerations in China from 2010 to 2019 from the perspective of economic geography. The study found that: (1) the green innovation efficiency of the three major urban agglomerations in China is in a fluctuating upward trend as a whole, with obvious spatial disequilibrium; (2) from the spatial point of view, the characteristics of global spatial agglomeration distribution have positive spatial correlation, and the law of local spatial autocorrelation is obvious, and the spatio-temporal pattern transitions from “low efficiency, big difference” to “high efficiency, small difference” during the study period; (3) there are obvious spatial spillover and diffusion effects on the green innovation efficiency of the three major urban agglomerations in China as a whole. However, the spatial dependence of green innovation efficiency is inconsistent in China’s three major urban agglomerations; the YRD Urban region and the PRD Urban region show a positive impact, while the JJJ Urban region shows a negative impact; (4) the level of economic development, the operating environment of science and technology, and the guiding factors of government system function with significant differences and regional spatial heterogeneity on the efficiency of green innovation in the three major urban agglomerations in China.

Spatiotemporal Differentiation and Influencing Factors of Green Technology Innovation Efficiency in the Construction Industry: A Case Study of Chengdu–Chongqing Urban Agglomeration

“…Secondly, green technology innovation in the construction sector has had an optimistic spillover effect in the study area, gradually transferring from the high-efficiency-level to the neighboring low-efficiency-level areas, and the low-efficiency-level area's scope gradually exhibiting a trend of narrowing. The findings of Hu et al (2022) [76], Wang et al (2022) [77], and Zhao et al (2021) [78] are in agreement with this finding. They believe that highefficiency areas have radiation effects on low-efficiency areas and narrow the gap between cities.…”

Assessing green production efficiency and spatial characteristics of China’s real estate industry based on the undesirable super-SBM model

“…Finally, the study of spatial evolution trends incorporated distribution dynamics methods, including random kernel density estimation (RKDE) and a spatial Markov chain (SMC). These methods facilitate depiction of the spatial structural evolution of China's green innovation capability 43 , 44 .…”

Exploration of Coupling Effects in the Digital Economy and Eco-Economic System Resilience in Urban Areas: Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration

“…By harnessing the power of the internet and inclusive finance to bring technological innovation effects and resource allocation effects into play, the digital economy enhances the rational sharing and equitable distribution of the wellbeing outcomes of economic development [44][45][46][47][48]. The scale, technology, and structural effects of digital economy development are amplified in terms of their impact on the resource environment [7,[49][50][51][52][53][54][55]. The digital economy reduces ecological pollution through the green development effect and innovation development effect, which in turn promotes eco-economic efficiency [56][57][58].…”