Analysis of spatial correlation network of China’s green innovation

中国 联动装置(软件) 绿色发展 经济地理学 业务 社会网络分析 政府(语言学) 分布(数学) 绿色创新 产业组织 技术创新 区域科学 经济增长 经济体制 地理 经济 政治学 数学 考古 化学 哲学 法学 数学分析 社会化媒体 基因 生物化学 语言学
作者
Jundi Fan,Zhenhong Xiao
出处
期刊:Journal of Cleaner Production [Elsevier]
卷期号:299: 126815-126815 被引量:98
标识
DOI:10.1016/j.jclepro.2021.126815
摘要

The rapid development of the global economy has caused severe environmental problems. Therefore, it is particularly important to focus on environmental protection and cleaner production as part of technological innovation. At present, China has not yet formed an efficient and systematic green innovation network, and thus, the efficiencies of regional clean production and green innovation still remain low. How to promote the development of a green innovation network has become an urgent issue in China. In this study, the SBM-DDF model, the gravity model , and the social network analysis model were used to analyze the spatial correlation network of China’s green innovation. The results showed the existence of spatial effects in China’s green innovation correlation network. The associated network is currently at a primary level of development, with a low network density and an annually increasing trend. In addition, China’s 30 provinces and cities were divided into four subgroups. The densities of each subgroup differed strongly and the distribution of innovation relationships was uneven. Moreover, regions with strong green technology innovation capabilities did not affect green innovation of other provinces or cities. Moreover, these regions obtained higher innovative linkage benefits from other provinces and cities. Furthermore, regions with medium innovation strength may play an important role within the green innovation linkage network. These results provide a new network perspective for the formulation of China’s green innovation policy. This can help to explain the current development status of China’s green innovation network and provides a theoretical basis for the government to formulate development directions and policies in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
paper发布了新的文献求助10
1秒前
科研通AI6应助仰望采纳,获得10
1秒前
健壮玉米完成签到,获得积分10
2秒前
张张完成签到,获得积分10
2秒前
2秒前
所所应助自信的雁开采纳,获得20
3秒前
3秒前
4秒前
4秒前
6秒前
6秒前
乐乐完成签到,获得积分10
7秒前
我是老大应助健壮玉米采纳,获得10
7秒前
量子星尘发布了新的文献求助10
8秒前
munire发布了新的文献求助30
8秒前
Yang_728发布了新的文献求助30
9秒前
俊逸的谷梦完成签到 ,获得积分20
9秒前
然然然完成签到 ,获得积分10
9秒前
huahua完成签到 ,获得积分10
9秒前
sunny发布了新的文献求助10
9秒前
9秒前
Cx270发布了新的文献求助10
10秒前
Lucas应助SS采纳,获得10
11秒前
11秒前
科目三应助zw采纳,获得30
12秒前
一顿能吃五大海碗完成签到,获得积分20
13秒前
张贵虎发布了新的文献求助10
14秒前
张悦宇完成签到,获得积分10
14秒前
14秒前
Jtui完成签到,获得积分10
14秒前
15秒前
星辰大海应助小鱼儿采纳,获得10
16秒前
慕青应助fduqyy采纳,获得30
17秒前
17秒前
chf完成签到,获得积分20
18秒前
111完成签到,获得积分20
18秒前
18秒前
开心的绮玉完成签到,获得积分10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Iron toxicity and hematopoietic cell transplantation: do we understand why iron affects transplant outcome? 2000
List of 1,091 Public Pension Profiles by Region 1021
Teacher Wellbeing: Noticing, Nurturing, Sustaining, and Flourishing in Schools 1000
A Technologist’s Guide to Performing Sleep Studies 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5481783
求助须知:如何正确求助?哪些是违规求助? 4582732
关于积分的说明 14386753
捐赠科研通 4511532
什么是DOI,文献DOI怎么找? 2472396
邀请新用户注册赠送积分活动 1458660
关于科研通互助平台的介绍 1432181