Research on the Ecological Innovation Efficiency of the Zhongyuan Urban Agglomeration: Measurement, Evaluation and Optimization
The objective of carbon peaking and carbon neutralization put forward higher requirements for the intensive use of energy and resources, and green and efficient development has become an essential part of high-quality development. Ecological innovation focuses on resource preservation and applicatio...
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Published in | Sustainability Vol. 15; no. 19; p. 14236 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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ISSN | 2071-1050 2071-1050 |
DOI | 10.3390/su151914236 |
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Abstract | The objective of carbon peaking and carbon neutralization put forward higher requirements for the intensive use of energy and resources, and green and efficient development has become an essential part of high-quality development. Ecological innovation focuses on resource preservation and application and the improvement of the ecological environment while driving economic development through innovation; therefore, ecological innovation has become a solution to balance resource conservation, environmental protection, and efficient development effectively and has received widespread attention. This research takes 30 cities of the Zhongyuan Urban Agglomeration as research subjects and constructs an urban agglomeration’s evaluation index system to measure ecological innovation efficiency. By utilizing the entropy-weight TOPSIS model and super-efficiency SBM-DEA model, the ecological innovation performance of the Zhongyuan Urban Agglomeration is measured and evaluated from 2006 to 2020; then, redundancy analysis is applied to analyze the correlation between ecological innovation inputs and outputs. The final results illustrate that: (1) The overall ecological innovation performance level of the Zhongyuan urban agglomeration is relatively low, and the ecological innovation ability of some cities is inadequate; (2) From the temporal perspective, the temporal evolution of the Zhongyuan urban agglomeration showed a less obvious U-shaped trend, and the innovation output benefits of the core development region are considerably superior to those of the co-development region, and the ecological innovation transformation efficiency of the Zhongyuan urban agglomeration shows a fluctuating trend; (3) From the spatial perspective, there are eight cities at the “high output and high efficiency” level but 19 cities at the “low output and low efficiency” level, and the ecological innovation performance of most cities in the north is obviously better than that in the south from the perspective of spatial distribution. Therefore, to further improve the ecological innovation ability and performance of the Zhongyuan urban agglomeration, relevant policies should be fully practiced and implemented, such as building Nanyang as a sub-central city, constructing an efficient ecological economy demonstration area in the south of Henan province, effectively integrating Zhengzhou and Kaifeng, and the innovative radiation of Zhengzhou as a national central city to other cities. |
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AbstractList | The objective of carbon peaking and carbon neutralization put forward higher requirements for the intensive use of energy and resources, and green and efficient development has become an essential part of high-quality development. Ecological innovation focuses on resource preservation and application and the improvement of the ecological environment while driving economic development through innovation; therefore, ecological innovation has become a solution to balance resource conservation, environmental protection, and efficient development effectively and has received widespread attention. This research takes 30 cities of the Zhongyuan Urban Agglomeration as research subjects and constructs an urban agglomeration’s evaluation index system to measure ecological innovation efficiency. By utilizing the entropy-weight TOPSIS model and super-efficiency SBM-DEA model, the ecological innovation performance of the Zhongyuan Urban Agglomeration is measured and evaluated from 2006 to 2020; then, redundancy analysis is applied to analyze the correlation between ecological innovation inputs and outputs. The final results illustrate that: (1) The overall ecological innovation performance level of the Zhongyuan urban agglomeration is relatively low, and the ecological innovation ability of some cities is inadequate; (2) From the temporal perspective, the temporal evolution of the Zhongyuan urban agglomeration showed a less obvious U-shaped trend, and the innovation output benefits of the core development region are considerably superior to those of the co-development region, and the ecological innovation transformation efficiency of the Zhongyuan urban agglomeration shows a fluctuating trend; (3) From the spatial perspective, there are eight cities at the “high output and high efficiency” level but 19 cities at the “low output and low efficiency” level, and the ecological innovation performance of most cities in the north is obviously better than that in the south from the perspective of spatial distribution. Therefore, to further improve the ecological innovation ability and performance of the Zhongyuan urban agglomeration, relevant policies should be fully practiced and implemented, such as building Nanyang as a sub-central city, constructing an efficient ecological economy demonstration area in the south of Henan province, effectively integrating Zhengzhou and Kaifeng, and the innovative radiation of Zhengzhou as a national central city to other cities. |
Audience | Academic |
Author | Wang, Yun Fu, Hao Yang, Yang Li, Simo Su, Zhaoxian Wang, Wenbin |
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SubjectTerms | Agglomeration Analysis Carbon China Data envelopment analysis Economic development Efficiency Emissions Energy consumption Innovations Linear programming Measurement Natural resources Production functions R&D Research & development Research methodology Sustainability Sustainable development |
Title | Research on the Ecological Innovation Efficiency of the Zhongyuan Urban Agglomeration: Measurement, Evaluation and Optimization |
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