Paper
24 October 2023 SE-SBM-DDF&MLI joint algorithm for analysis of spatiotemporal differentiation and driving factors of urban GTFP in Guangdong
Yi Tang, Xianchi Huang, Jie Zhao, Yingqi Tan
Author Affiliations +
Proceedings Volume 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023); 128042H (2023) https://doi.org/10.1117/12.3006357
Event: 2nd International Conference on Sustainable Technology and Management (ICSTM2023), 2023, Dongguan, China
Abstract
Guangdong is one of the most open-minded and economically active regional economic centers in mainland China, and significantly impacts the global economic landscape. In this paper, environmental factors have been integrated into the analytical framework of total factor productivity, SE-SBM-DDF model is constructed, and annual data of 21 cities in Guangdong from 2010 to 2019 are collected to estimate the city-annual efficiency value reflecting green total factor productivity (GTFP for short). It is found that shenzhen, Maoming, Shanwei and Chaozhou have the highest GTFP, among which Shenzhen has the highest GTFP. Jiangmen, Huizhou, Qingyuan and Shaoguan had the lowest GTFP, of which Shaoguan had the lowest. By regional analysis, GTFP is higher in East and west Guangdong, lowest in north Guangdong, and middle in Pearl River Delta. On the whole, the efficiency value and GTFP of Guangdong exhibited a decline from 2010 to 2015, and the change was stable from 2015 to 2019. The ML index reflecting the change of green TFP is further constructed, and it is found that among the 21 cities, Jieyang, Yangjiang, Zhaoqing, Shenzhen and Heyuan have the GML index of more than 1.0, and the GML index of Jieyang, Yangjiang, Zhaoqing and Heyuan is the highest, and their green TFP is increased, and the increase is the largest; On the other hand, the ML index of Zhongshan, Zhuhai, Dongguan, ShanTou and Meizhou is lower than 1.0 and lowest, and their GTFP is declining and dropping fastest. After further decomposition of the GML index, it is found that the change of GML index, that is, the change of GTFP, is mainly affected by the progress of technical efficiency in individual cities, while the change of GTFP is mainly driven by the progress of technology in different regions or Guangdong Province as a whole. The findings of this study carry significant implications for the high quality development of Guangdong and the construction of "green beautiful Guangdong".
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yi Tang, Xianchi Huang, Jie Zhao, and Yingqi Tan "SE-SBM-DDF&MLI joint algorithm for analysis of spatiotemporal differentiation and driving factors of urban GTFP in Guangdong", Proc. SPIE 12804, Second International Conference on Sustainable Technology and Management (ICSTM 2023), 128042H (24 October 2023); https://doi.org/10.1117/12.3006357
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KEYWORDS
Reflection

Industry

Analytical research

Neodymium

Carbon

Data modeling

Decision making

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