Governance of rural solid waste under a multi-subject governance model

Rural solid waste (RSW) exhibits distinct characteristics compared to municipal solid waste (MSW), such as dispersed distribution, long governance chains, and low recycling value, making it unsuitable to apply the same management measures as MSW. Government-led RSW management results in excessive administrative costs, and the inherent characteristics of RSW reduce market enthusiasm for its management. To address these issues, this paper integrates the “ multi-subject governance “ model with RSW management and establishes a systematic evaluation index system for RSW governance. Utilizing the Best-Worst Method (BWM), key factors were identified. Utilizing the VIKOR method, representative provinces in China were used as case studies to validate the scientific nature of the evaluation indices. The research findings indicate that the multi-subject governance model is an effective approach for RSW management. Key factors influencing RSW management effectiveness include various governmental measures, waste sorting, and a long-term multi-subject governance mechanism. Case analysis reveals a strong correlation between the level of economic development and the effectiveness of RSW management. However, constructing a government-led, multi-subject collaborative urban-rural interconnected RSW management model can effectively address RSW management issues in economically underdeveloped areas. This research provides innovative solutions for RSW management, contributing to high-quality and sustainable development in rural areas.

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Publication Details

Journal
Scientific Reports
Published
2024-11-07
DOI
https://doi.org/10.1038/s41598-024-78732-5
Citations
6
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
1.76
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article

Governance of rural solid waste under a multi-subject governance model

Danlan Xie, Hao Liang, Dongshi Sun
6 citations
Scientific Reports
Municipal Solid Waste Management
1.76
article

Governance of rural solid waste under a multi-subject governance model

Danlan Xie, Hao Liang, Dongshi Sun
article en
6 citations

Abstract

Rural solid waste (RSW) exhibits distinct characteristics compared to municipal solid waste (MSW), such as dispersed distribution, long governance chains, and low recycling value, making it unsuitable to apply the same management measures as MSW. Government-led RSW management results in excessive administrative costs, and the inherent characteristics of RSW reduce market enthusiasm for its management. To address these issues, this paper integrates the “ multi-subject governance “ model with RSW management and establishes a systematic evaluation index system for RSW governance. Utilizing the Best-Worst Method (BWM), key factors were identified. Utilizing the VIKOR method, representative provinces in China were used as case studies to validate the scientific nature of the evaluation indices. The research findings indicate that the multi-subject governance model is an effective approach for RSW management. Key factors influencing RSW management effectiveness include various governmental measures, waste sorting, and a long-term multi-subject governance mechanism. Case analysis reveals a strong correlation between the level of economic development and the effectiveness of RSW management. However, constructing a government-led, multi-subject collaborative urban-rural interconnected RSW management model can effectively address RSW management issues in economically underdeveloped areas. This research provides innovative solutions for RSW management, contributing to high-quality and sustainable development in rural areas.

Scientific ReportsVol. 14(1)
Dalian Neusoft University of Information (CN), Zhejiang Gongshang University Hangzhou College of Commerce, Zhejiang Gongshang University (CN)
Openalex Percentile: Top 16%
Municipal Solid Waste Management
1.76
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Governance of rural solid waste under a multi-subject governance model — Danlan Xie, Hao Liang, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS