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Research articles

Ecological efficiency assessment under the construction of low-carbon city: a perspective of green technology innovation

, , ORCID Icon & ORCID Icon
Pages 1727-1752 | Received 26 Sep 2020, Accepted 15 Jun 2021, Published online: 25 Aug 2021
 

Abstract

This paper develops a novel hybrid Trigonometric Envelopment Analysis for Ideal Solutions (TEA-IS) model to assess the ecological efficiency of 248 Chinese cities for a 14-year period and employs a difference-in-difference approach to reveal the mechanism of the impact of low-carbon pilot city policies on ecological efficiency from the perspective of green technology innovation. This TEA-IS approach not only combines the advantageous features that exist in each individual model, but also allows an analysis of ecological efficiency in terms of the synergistic effects that may exist among correlated positive and negative criteria. Machine learning methods are also employed to predict high-low performance and synergistic Chinese cities in terms of the socio-economic and demographic context. Results indicate that ecological efficiency is generally low in Chinese cities. The low-carbon pilot city policy does help to improve ecological efficiency, which results from the mechanism of green technology innovation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Enhanced Actions on Climate Change: China’s Intended Nationally Determined Contributions.

Additional information

Funding

We thank the support provided by the Natural Science Foundation of Guangdong Province of China (2021B1515020103), the National Natural Science Foundation of China (72003071), Guangdong Province Colleges and Universities Young Innovative Talent Project (2020WQNCX012), the Key Project of Philosophy and Social Sciences Research of the Ministry of Education of China (17JZD013), Guangdong Provincial Soft Science Research Project (2020A1010020031), and Guangdong-Hong Kong-Macao Environmental Quality Collaborative Innovation Laboratory Project (GHML2021-701).

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