Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China
The growing intricacy and expansion of the transportation network structure present challenges to achieving low-carbon development and sustainable growth in China's regional transportation industry. This study employs the super-efficiency SBM model and social network analysis to examine the mec...
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| Language: | English |
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Elsevier
2025-06-01
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| Series: | Sustainable Futures |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666188825002199 |
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| author | Lin Liu Yuming Liu Rong Zhao |
| author_facet | Lin Liu Yuming Liu Rong Zhao |
| author_sort | Lin Liu |
| collection | DOAJ |
| description | The growing intricacy and expansion of the transportation network structure present challenges to achieving low-carbon development and sustainable growth in China's regional transportation industry. This study employs the super-efficiency SBM model and social network analysis to examine the mechanistic formation of carbon emission networks, emphasizing temporal and gradient distribution patterns of efficiency networks, spatial transfer pathways, efficiency evolution characteristics, and the complexity of microstructures. Findings reveal: (1) The overall efficiency of carbon emissions exhibits a “N-shaped” trend over time, driven by local high efficiency inducing overall high-efficiency output. (2) Regional imbalances persist, characterized by a “λ-shaped” fixed radiation pattern centered around Beijing, with spatial transmission from eastern coastal areas to north-south transfer to western diffusion. The central region lacks a well-structured efficiency guidance system. (3) A multi-level composite network system exists among provinces, featuring a coordination network as the primary component and backbone network as secondary element. The coordination network serves as a stable driving force, enhancing efficiency network density, with increased robustness in the central and eastern regions and a closed connectivity structure in the northwest. (4) Internal node differences contribute to uneven development; nodes jointly formed with Beijing act as gatekeepers, controlling medium and high efficiency networks in the eastern, central, and northern regions. The “One super-Five strong” nodes and “Two Zones – Four Wings” alliance generate significant external connectivity, enhancing network complexity and resilience. The study proposes policy recommendations, focusing on optimizing the transportation network structure and carbon emission rights market trading to improve carbon emission efficiency. |
| format | Article |
| id | doaj-art-fef3a27ea5094122a9ab9ee908d37f74 |
| institution | Kabale University |
| issn | 2666-1888 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Sustainable Futures |
| spelling | doaj-art-fef3a27ea5094122a9ab9ee908d37f742025-08-20T03:31:20ZengElsevierSustainable Futures2666-18882025-06-01910065110.1016/j.sftr.2025.100651Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from ChinaLin Liu0Yuming Liu1Rong Zhao2School of Economics and Management, Beijing Jiaotong University, Haidian District, Beijing 100044, China; Corresponding author.School of Economics and Management, Beijing Jiaotong University, Haidian District, Beijing 100044, ChinaChina Academy of Building Research, Beijing, ChinaThe growing intricacy and expansion of the transportation network structure present challenges to achieving low-carbon development and sustainable growth in China's regional transportation industry. This study employs the super-efficiency SBM model and social network analysis to examine the mechanistic formation of carbon emission networks, emphasizing temporal and gradient distribution patterns of efficiency networks, spatial transfer pathways, efficiency evolution characteristics, and the complexity of microstructures. Findings reveal: (1) The overall efficiency of carbon emissions exhibits a “N-shaped” trend over time, driven by local high efficiency inducing overall high-efficiency output. (2) Regional imbalances persist, characterized by a “λ-shaped” fixed radiation pattern centered around Beijing, with spatial transmission from eastern coastal areas to north-south transfer to western diffusion. The central region lacks a well-structured efficiency guidance system. (3) A multi-level composite network system exists among provinces, featuring a coordination network as the primary component and backbone network as secondary element. The coordination network serves as a stable driving force, enhancing efficiency network density, with increased robustness in the central and eastern regions and a closed connectivity structure in the northwest. (4) Internal node differences contribute to uneven development; nodes jointly formed with Beijing act as gatekeepers, controlling medium and high efficiency networks in the eastern, central, and northern regions. The “One super-Five strong” nodes and “Two Zones – Four Wings” alliance generate significant external connectivity, enhancing network complexity and resilience. The study proposes policy recommendations, focusing on optimizing the transportation network structure and carbon emission rights market trading to improve carbon emission efficiency.http://www.sciencedirect.com/science/article/pii/S2666188825002199Transportation industryCarbon emissionsEfficiency networkSpatial correlationCarbon transmission |
| spellingShingle | Lin Liu Yuming Liu Rong Zhao Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China Sustainable Futures Transportation industry Carbon emissions Efficiency network Spatial correlation Carbon transmission |
| title | Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China |
| title_full | Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China |
| title_fullStr | Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China |
| title_full_unstemmed | Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China |
| title_short | Transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis: Evidence from China |
| title_sort | transportation carbon emission efficiency network formation mechanism and spatial structural complexity analysis evidence from china |
| topic | Transportation industry Carbon emissions Efficiency network Spatial correlation Carbon transmission |
| url | http://www.sciencedirect.com/science/article/pii/S2666188825002199 |
| work_keys_str_mv | AT linliu transportationcarbonemissionefficiencynetworkformationmechanismandspatialstructuralcomplexityanalysisevidencefromchina AT yumingliu transportationcarbonemissionefficiencynetworkformationmechanismandspatialstructuralcomplexityanalysisevidencefromchina AT rongzhao transportationcarbonemissionefficiencynetworkformationmechanismandspatialstructuralcomplexityanalysisevidencefromchina |