{"title":"Spatial network characteristics and driving factors of low-carbon technology innovation efficiency in northern China","authors":"Dongri Han , Yuhan Li , Yingying Geng","doi":"10.1016/j.uclim.2025.102529","DOIUrl":null,"url":null,"abstract":"<div><div>China's ecological civilization construction has entered a critical period with carbon reduction as the key strategic direction. Exploring the network structure of low-carbon technology innovation efficiency can offer a scientific basis and practical reference for advancing national green and low-carbon development. Taking 131 prefecture-level cities in the northern region as research objects, this paper employs the accelerated genetic algorithm-based projection pursuit model, modified gravity model and social network analysis to explore the spatial network correlation characteristics and influencing factors of low-carbon technology innovation efficiency during 2010–2023. The results show that the low-carbon technology innovation efficiency in the northern region presents a pattern of “the east region > the central region > the northeast region > the west region”, with local dynamic characteristics and unbalanced characteristics co-existing. The overall network density of low-carbon technology innovation efficiency in the northern region presents a pattern of “the east region > the central region > the northeast region > the west region”, with obvious node characteristics. As time passes, the overall network structure of the spatial correlation of low-carbon technology innovation efficiency in the northern region develops toward the trend of density, diversification and robustness. The bidirectional overflow plate is developing rapidly. Beijing, Tianjin, Jinan and Zhengzhou have become important central cities to radiate and drive the development of surrounding areas. The spatial convergence analysis shows that the convergence characteristics and catch-up effect of low-carbon technology innovation efficiency of cities in the northern region are significant. Environmental regulation, reserve of innovative talents, innovation environment and FDI emerge as important factors influencing the formation and development of low-carbon technology innovation efficiency network in the northern region.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"62 ","pages":"Article 102529"},"PeriodicalIF":6.0000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Urban Climate","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212095525002457","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
China's ecological civilization construction has entered a critical period with carbon reduction as the key strategic direction. Exploring the network structure of low-carbon technology innovation efficiency can offer a scientific basis and practical reference for advancing national green and low-carbon development. Taking 131 prefecture-level cities in the northern region as research objects, this paper employs the accelerated genetic algorithm-based projection pursuit model, modified gravity model and social network analysis to explore the spatial network correlation characteristics and influencing factors of low-carbon technology innovation efficiency during 2010–2023. The results show that the low-carbon technology innovation efficiency in the northern region presents a pattern of “the east region > the central region > the northeast region > the west region”, with local dynamic characteristics and unbalanced characteristics co-existing. The overall network density of low-carbon technology innovation efficiency in the northern region presents a pattern of “the east region > the central region > the northeast region > the west region”, with obvious node characteristics. As time passes, the overall network structure of the spatial correlation of low-carbon technology innovation efficiency in the northern region develops toward the trend of density, diversification and robustness. The bidirectional overflow plate is developing rapidly. Beijing, Tianjin, Jinan and Zhengzhou have become important central cities to radiate and drive the development of surrounding areas. The spatial convergence analysis shows that the convergence characteristics and catch-up effect of low-carbon technology innovation efficiency of cities in the northern region are significant. Environmental regulation, reserve of innovative talents, innovation environment and FDI emerge as important factors influencing the formation and development of low-carbon technology innovation efficiency network in the northern region.
期刊介绍:
Urban Climate serves the scientific and decision making communities with the publication of research on theory, science and applications relevant to understanding urban climatic conditions and change in relation to their geography and to demographic, socioeconomic, institutional, technological and environmental dynamics and global change. Targeted towards both disciplinary and interdisciplinary audiences, this journal publishes original research papers, comprehensive review articles, book reviews, and short communications on topics including, but not limited to, the following:
Urban meteorology and climate[...]
Urban environmental pollution[...]
Adaptation to global change[...]
Urban economic and social issues[...]
Research Approaches[...]