Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China
Exploring the management efficiency of construction and demolition waste (CDW) and the spatial correlation network across regions in China is essential for promoting sustainable development and optimizing resource allocation. This study utilizes an improved three-stage SBM-DEA model and social netwo...
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MDPI AG
2024-12-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/15/1/51 |
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| author | Xueying Yang Shiping Wen |
| author_facet | Xueying Yang Shiping Wen |
| author_sort | Xueying Yang |
| collection | DOAJ |
| description | Exploring the management efficiency of construction and demolition waste (CDW) and the spatial correlation network across regions in China is essential for promoting sustainable development and optimizing resource allocation. This study utilizes an improved three-stage SBM-DEA model and social network analysis to examine the management efficiency of CDW across 30 regions in China from 2010 to 2020. Research findings indicate that from 2010 to 2020, China’s CDW management efficiency improved, with a clear spatial gradient observed across regions. The eastern regions performed better than the western, northeastern, and central areas. Key factors affecting CDW management efficiency include economic development, infrastructure expansion, government policies, and technological progress. Economic growth was negatively associated with redundancy in labor and machinery, while infrastructure development correlated positively with labor, machinery, and capital redundancy. In some areas, government policies contributed to excessive capital investment, increasing redundancy. Technological progress helped reduce labor and machinery redundancy but had a minimal impact on capital redundancy. The spatial correlation network of CDW management demonstrated a “small-world” structure, maintaining stability in network density, relatedness, and hierarchy, though the network efficiency showed a downward trend. Beijing, Henan, and Xinjiang stood out as key nodes in the network, performing strongly in various centrality measures. |
| format | Article |
| id | doaj-art-1e1b83d346a64f219c5005ecba69d9b3 |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Buildings |
| spelling | doaj-art-1e1b83d346a64f219c5005ecba69d9b32025-01-10T13:15:53ZengMDPI AGBuildings2075-53092024-12-011515110.3390/buildings15010051Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in ChinaXueying Yang0Shiping Wen1School of Economics and Management, Changchun University of Technology, Changchun 130012, ChinaSchool of Management, Chongqing University of Science and Technology, Chongqing 401331, ChinaExploring the management efficiency of construction and demolition waste (CDW) and the spatial correlation network across regions in China is essential for promoting sustainable development and optimizing resource allocation. This study utilizes an improved three-stage SBM-DEA model and social network analysis to examine the management efficiency of CDW across 30 regions in China from 2010 to 2020. Research findings indicate that from 2010 to 2020, China’s CDW management efficiency improved, with a clear spatial gradient observed across regions. The eastern regions performed better than the western, northeastern, and central areas. Key factors affecting CDW management efficiency include economic development, infrastructure expansion, government policies, and technological progress. Economic growth was negatively associated with redundancy in labor and machinery, while infrastructure development correlated positively with labor, machinery, and capital redundancy. In some areas, government policies contributed to excessive capital investment, increasing redundancy. Technological progress helped reduce labor and machinery redundancy but had a minimal impact on capital redundancy. The spatial correlation network of CDW management demonstrated a “small-world” structure, maintaining stability in network density, relatedness, and hierarchy, though the network efficiency showed a downward trend. Beijing, Henan, and Xinjiang stood out as key nodes in the network, performing strongly in various centrality measures.https://www.mdpi.com/2075-5309/15/1/51CDW management efficiencythree-stage SBM-DEA modelsocial network analysisspatial correlation network |
| spellingShingle | Xueying Yang Shiping Wen Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China Buildings CDW management efficiency three-stage SBM-DEA model social network analysis spatial correlation network |
| title | Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China |
| title_full | Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China |
| title_fullStr | Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China |
| title_full_unstemmed | Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China |
| title_short | Spatial Correlation Network of Construction and Demolition Waste Management Efficiency: A Study Based on an Improved Three-Stage SBM-DEA Model in China |
| title_sort | spatial correlation network of construction and demolition waste management efficiency a study based on an improved three stage sbm dea model in china |
| topic | CDW management efficiency three-stage SBM-DEA model social network analysis spatial correlation network |
| url | https://www.mdpi.com/2075-5309/15/1/51 |
| work_keys_str_mv | AT xueyingyang spatialcorrelationnetworkofconstructionanddemolitionwastemanagementefficiencyastudybasedonanimprovedthreestagesbmdeamodelinchina AT shipingwen spatialcorrelationnetworkofconstructionanddemolitionwastemanagementefficiencyastudybasedonanimprovedthreestagesbmdeamodelinchina |