Abstract
As an effective method for achieving sustainable development, green innovation plays a key role in promoting regional integration and high-quality development in the Yangtze River Delta region. Using the Super-SBM DEA model of undesirable outputs to measure the green innovation efficiency of 41 cities in the Yangtze River Delta from 2011 to 2019, and constructing the correlation matrix of green innovation efficiency among cities by gravity model, this paper discusses the spatial correlation, network structure characteristics and driving factors of green innovation efficiency by applying social network analysis method. The results show that: (1) The efficiency of urban green innovation in the Yangtze River Delta is basically fluctuated and increased. There is obvious regional heterogeneity in efficiency, and the distribution pattern is high in the south but low in the north. (2) The spatial association network of green innovation efficiency in the region is complex and the local associations of some cities are strong. In some regional central cities, such as Shanghai, the effect of syphon aspect is obvious, while the spillover effect needs to be improved. (3) The efficiency network presents an obvious core-edge structure. The core area is mainly concentrated in Shanghai, other provincial capitals and surrounding cities, which basically presents a trend distribution with “most concentrated, a few dispersed” . (4) The differences in patent output and industrial structure have a significant positive effect on the spatial correlation intensity of green innovation efficiency among cities. The differences in environmental quality and geographical distance have negative effects on the spatial correlation of green innovation efficiency among cities. These factors become important factors affecting the spatial network structure of urban green innovation efficiency in the Yangtze River Delta.
| Translated title of the contribution | Evolution and Driving Factors of Spatial Network Structure of Green Innovation Efficiency in Yangtze River Delta |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1335-1348 |
| Number of pages | 14 |
| Journal | Resources and Environment in the Yangtze Basin |
| Volume | 32 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2023 |