Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry
To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China’s construction industry, this paper measures the carbon emission data of China’s construction industry in various provinces from 2006 to 2017 and then combines the modified gravity mode...
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| Materialtyp: | Artikel |
| Språk: | English |
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MDPI AG
2022-02-01
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| Serie: | Buildings |
| Ämnen: | |
| Länkar: | https://www.mdpi.com/2075-5309/12/2/201 |
| _version_ | 1827656413564895232 |
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| author | Zhenshuang Wang Yanxin Zhou Ning Zhao Tao Wang Zhongsheng Zhang |
| author_facet | Zhenshuang Wang Yanxin Zhou Ning Zhao Tao Wang Zhongsheng Zhang |
| author_sort | Zhenshuang Wang |
| collection | DOAJ |
| description | To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China’s construction industry, this paper measures the carbon emission data of China’s construction industry in various provinces from 2006 to 2017 and then combines the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of the carbon emission intensity in China’s construction industry. The results show that the regional differences of the carbon emissions of the construction industry are significant, and the carbon emission intensity of the construction industry shows a fluctuating trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, and the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase in network density and the decrease in network hierarchy and network efficiency will reduce the construction carbon emission intensity. |
| first_indexed | 2024-03-09T22:25:10Z |
| format | Article |
| id | doaj.art-87288fbc6db743588cad361e9feb2cc4 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T22:25:10Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-87288fbc6db743588cad361e9feb2cc42023-11-23T19:06:32ZengMDPI AGBuildings2075-53092022-02-0112220110.3390/buildings12020201Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction IndustryZhenshuang Wang0Yanxin Zhou1Ning Zhao2Tao Wang3Zhongsheng Zhang4School of Investment and Construction Management, Dongbei University of Finance and Economics, Dalian 116025, ChinaSchool of Investment and Construction Management, Dongbei University of Finance and Economics, Dalian 116025, ChinaSchool of Finance, Dongbei University of Finance and Economics, Dalian 116025, ChinaSchool of Public and Policy Administration, Chongqing University, Chongqing 400044, ChinaSchool of Investment and Construction Management, Dongbei University of Finance and Economics, Dalian 116025, ChinaTo explore the spatial network structure characteristics and driving effects of carbon emission intensity in China’s construction industry, this paper measures the carbon emission data of China’s construction industry in various provinces from 2006 to 2017 and then combines the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of the carbon emission intensity in China’s construction industry. The results show that the regional differences of the carbon emissions of the construction industry are significant, and the carbon emission intensity of the construction industry shows a fluctuating trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, and the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase in network density and the decrease in network hierarchy and network efficiency will reduce the construction carbon emission intensity.https://www.mdpi.com/2075-5309/12/2/201carbon emission intensitygravity modelsocial networkdriving effectregional differenceconstruction industry |
| spellingShingle | Zhenshuang Wang Yanxin Zhou Ning Zhao Tao Wang Zhongsheng Zhang Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry Buildings carbon emission intensity gravity model social network driving effect regional difference construction industry |
| title | Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry |
| title_full | Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry |
| title_fullStr | Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry |
| title_full_unstemmed | Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry |
| title_short | Spatial Correlation Network and Driving Effect of Carbon Emission Intensity in China’s Construction Industry |
| title_sort | spatial correlation network and driving effect of carbon emission intensity in china s construction industry |
| topic | carbon emission intensity gravity model social network driving effect regional difference construction industry |
| url | https://www.mdpi.com/2075-5309/12/2/201 |
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