{"title":"中国多尺度绿色创新的动态演变与趋势预测","authors":"Xiaohua Xin , Lachang Lyu , Yanan Zhao","doi":"10.1016/j.geosus.2023.05.001","DOIUrl":null,"url":null,"abstract":"<div><p>Numerous studies deal with spatial analysis of green innovation (GI). However, researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China. This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000–2019. We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales, including regional, provincial, and prefectural. Additionally, we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development. The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale, with significant spatial differences of GI decreasing in each scale. Furthermore, the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales, exhibiting the “club convergence” effect and a tendency to transfer to higher levels of proximity. This effect is more pronounced on a larger scale, but it is increasingly challenging to transfer to higher levels. The study also indicates a steady and sustained growth of GI in China, which concentrates on higher levels over time. These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.</p></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"4 3","pages":"Pages 222-231"},"PeriodicalIF":8.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic evolution and trend prediction of multi-scale green innovation in China\",\"authors\":\"Xiaohua Xin , Lachang Lyu , Yanan Zhao\",\"doi\":\"10.1016/j.geosus.2023.05.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Numerous studies deal with spatial analysis of green innovation (GI). However, researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China. This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000–2019. We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales, including regional, provincial, and prefectural. Additionally, we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development. The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale, with significant spatial differences of GI decreasing in each scale. Furthermore, the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales, exhibiting the “club convergence” effect and a tendency to transfer to higher levels of proximity. This effect is more pronounced on a larger scale, but it is increasingly challenging to transfer to higher levels. The study also indicates a steady and sustained growth of GI in China, which concentrates on higher levels over time. These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.</p></div>\",\"PeriodicalId\":52374,\"journal\":{\"name\":\"Geography and Sustainability\",\"volume\":\"4 3\",\"pages\":\"Pages 222-231\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geography and Sustainability\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666683923000299\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geography and Sustainability","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666683923000299","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
Dynamic evolution and trend prediction of multi-scale green innovation in China
Numerous studies deal with spatial analysis of green innovation (GI). However, researchers have paid limited attention to analyzing the multi-scale evolution patterns and predicting trends of GI in China. This paper seeks to address this research gap by examining the multi-scale distribution and evolutionary characteristics of GI activities based on the data from 337 cities in China during 2000–2019. We used scale variance and the two-stage nested Theil decomposition method to examine the spatial distribution and inequalities of GI in China at multiple scales, including regional, provincial, and prefectural. Additionally, we utilized the Markov chain and spatial Markov chain to explore the dynamic evolution of GI in China and predict its long-term development. The findings indicate that GI in China has a multi-scale effect and is highly sensitive to changes in spatial scale, with significant spatial differences of GI decreasing in each scale. Furthermore, the spatiotemporal evolution of GI is influenced by both geospatial patterns and spatial scales, exhibiting the “club convergence” effect and a tendency to transfer to higher levels of proximity. This effect is more pronounced on a larger scale, but it is increasingly challenging to transfer to higher levels. The study also indicates a steady and sustained growth of GI in China, which concentrates on higher levels over time. These results contribute to a more precise understanding of the scale at which GI develops and provide a scientific basis and policy suggestions for optimizing the spatial structure of GI and promoting its development in China.
期刊介绍:
Geography and Sustainability serves as a central hub for interdisciplinary research and education aimed at promoting sustainable development from an integrated geography perspective. By bridging natural and human sciences, the journal fosters broader analysis and innovative thinking on global and regional sustainability issues.
Geography and Sustainability welcomes original, high-quality research articles, review articles, short communications, technical comments, perspective articles and editorials on the following themes:
Geographical Processes: Interactions with and between water, soil, atmosphere and the biosphere and their spatio-temporal variations;
Human-Environmental Systems: Interactions between humans and the environment, resilience of socio-ecological systems and vulnerability;
Ecosystem Services and Human Wellbeing: Ecosystem structure, processes, services and their linkages with human wellbeing;
Sustainable Development: Theory, practice and critical challenges in sustainable development.