ORIGINAL RESEARCH
Dynamic Evolution and Regional Differences
in Ecological Welfare Performance: Insights
from Guangdong Province, China
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1
Shunde Polytechnic , Desheng East Road, Shunde District, Foshan City, Guangdong Province
2
City University of Macau , Avenida Padre Tomas Pereira Taipa Macau
3
Guangdong University of Petrochemical Technology, 139 Guandu Second Road, Maoming City, Guangdong Province
Submission date: 2023-12-04
Final revision date: 2024-02-29
Acceptance date: 2024-03-24
Online publication date: 2024-06-20
Corresponding author
Chunyuan Ke
City University of Macau , Avenida Padre Tomas Pereira Taipa Macau
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ABSTRACT
Ecological Welfare Performance (EWP) is a core issue in sustainable development and ecological
civilization. Although Guangdong Province is one of China’s most developed economies and
most highly urbanized areas, there is a gap in the evaluation of the ecological welfare performance
of the province. Previous studies have mainly calculated the performance of ecological welfare
from a static viewpoint or only from the perspective of network efficiency, and few researchers have
considered dynamic characteristics and network structures. This research focuses on 21 prefecturelevel
cities in Guangdong Province and measures their ecological welfare performance by applying
the dynamic network slacks-based measure (DNSBM) model. Using the Dagum Gini coefficient,
this study identifies the sources and contributions of differences in ecological welfare performance
among regions in Guangdong Province. The results reveal a low overall level of ecological welfare, with
levels of ecological welfare showing an uneven distribution among the 21 cities. EWP and economic
growth are spatially mismatched. The overall variations in the ecological welfare performance in the
province are mainly due to ultra-high-density contributions. Therefore, we recommend that Guangdong
Province strengthen overall regional coordinated development and promote high-quality “shared”
development in the northern, eastern, and western areas.