Tong Zhang

Work place: School of Science, Chongqing University of Technology, Chongqing, 400054, China

E-mail: zhangtong@stu.cqut.edu.cn

Website:

Research Interests: Machine Learning

Biography

Tong Zhang is a current Master's degree student in Applied Statistics at the College of Science, Chongqing Polytechnic University, Chongqing, China. Her research interests are mainly in machine learning and spatio-temporal data.

 

Author Articles
Spatio-temporal Dynamic Evolution and Inhibiting Factor Analysis of TFEE in the CCTC Economic Circle

By Shiyi Zeng Liyun Su Tong Zhang Junjie Peng Xiangjing Li Feng Zhao Dongyang Qiu

DOI: https://doi.org/10.5815/ijieeb.2024.01.01, Pub. Date: 8 Feb. 2024

Accounting for 30.8% of the total economic volume of the western region by 2021, the "fourth pole" of China's economic development is progressively being established as the Chengdu-Chongqing twin-city(CCTC) Zone. Therefore, increasing Total Factor Energy Efficiency (TFEE) and reducing the disparities in energy efficiency amongst cities in the area are important for the economic development of the CCTC Economic Zone. Accordingly, this study employs an output-oriented, super-efficient DEA model with constant returns to scale to measure the total factor energy efficiency of 16 prefecture-level cities in the CCTC economic circle from 2006 to 2020. It also examines the spatial distribution and variation patterns of each city's prefecture-level total factor energy efficiency. Then, spatial autocorrelation and random forest were used to explore the interrelationship among the indicators of the drivers, and the variables were screened according to Gini importance, finally, PCA-GWR models and spatial panel regression models were constructed to dissect the key drivers. The empirical findings indicate that: (1) the average energy efficiency of Chongqing and Chengdu is only 0.708 and 0.788, and the overall efficiency shows a steady increase from 2009 to 2018. (2) The spatial distribution is mainly as follows: H-H agglomerations are distributed in the northeastern cities of the CCTC Economic Zone, L-L agglomerations are distributed in the south, H-L agglomerations and L-H agglomerations are distributed in the north-central part of Chengdu-Chongqing Economic Zone. (3) Industrial structure, population structure, and governmental behavior have significant effects on energy efficiency, with a population mortality rate as the inhibiting factor and the proportion of tertiary industry and policy behavior as the contributing factors. Based on the empirical findings, it is recommended to accelerate the industrial structure adjustment, implement the CCTC economic circle's core cities' target of energy-saving, and build a "community" bridge to improve energy efficiency and promote economic development.

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