Disparities in Environmental Behavior from Urban–Rural Perspectives: How Socioeconomic Status Structures Influence Residents’ Environmental Actions—Based on the 2021 China General Social Survey Data

This study explores the environmental behavior disparities between urban and rural residents in China due to socioeconomic status differences amidst social governance and institutional reform. Using OLS regression models on the 2021 China General Social Survey (CGSS) data, it analyzes the impact of...

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Veröffentlicht in:Sustainability 2024-09, Vol.16 (18), p.7886
Hauptverfasser: Cheng, Hui, Mao, Chunmei
Format: Artikel
Sprache:eng
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Zusammenfassung:This study explores the environmental behavior disparities between urban and rural residents in China due to socioeconomic status differences amidst social governance and institutional reform. Using OLS regression models on the 2021 China General Social Survey (CGSS) data, it analyzes the impact of socioeconomic status on environmental behaviors. This study reveals that urban residents generally exhibit better environmental behaviors than rural residents. Education and income are identified as critical drivers, with education raising environmental awareness and income driving participation in environmental activities. Urban residents benefit more from these factors. The policy recommendations are for the government to enhance rural education resources and improve education quality, ensuring that education poverty alleviation policies are effectively implemented to support rural development. Simultaneously, promoting rural economic growth and narrowing the urban–rural economic gap is crucial for improving rural environmental behavior and achieving urban–rural environmental harmony. Furthermore, the results call on the international community to focus on environmental governance systems, aiming to provide references for other developing countries in formulating environmental policies, thereby promoting the creation of a more just, eco-friendly, and sustainable global development framework.
ISSN:2071-1050
2071-1050
DOI:10.3390/su16187886