A Multi-Level Grey Evaluation of the Eco-industrial Development Level of Industrial Parks Based on a Combination of Coefficient of Variation and AHM Weighting

To support environmental management and differentiated green transformation in industrial parks, this study develops an evaluation framework that assesses eco-industrial development performance and identifies park-specific strengths and weaknesses. The framework contains 39 indicators across economic development, ecological environment, material circulation, resource potential, technological innovation, and policy and management. Weights are derived using the Attribute Hierarchical Model (AHM) and coefficient of variation method, integrated via the minimum-deviation principle, and applied through multi-level grey evaluation to four Chinese parks. Findings show that policy and management is weighted highest, followed by economic development and ecological environment; overall performance ranks Tianjin, Suzhou, Dalian, and Fushun. Critically, similar aggregate performance masks distinct weaknesses in environmental governance, resource circulation, technological innovation, and resource conditions. The framework therefore enables diagnosis of differentiated management priorities and supports park-specific pathways toward eco-industrial development.

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Publication Details

Journal
Journal of Sustainable Development
Published
2026-11-05
DOI
https://doi.org/10.5539/jsd.v19n6p119
Primary Topic
Sustainable Industrial Ecology
Type
article
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article

A Multi-Level Grey Evaluation of the Eco-industrial Development Level of Industrial Parks Based on a Combination of Coefficient of Variation and AHM Weighting

Yilu Shang, Yucen Liu
Journal of Sustainable Development
Sustainable Industrial Ecology
article

A Multi-Level Grey Evaluation of the Eco-industrial Development Level of Industrial Parks Based on a Combination of Coefficient of Variation and AHM Weighting

Yilu Shang, Yucen Liu
article en

Abstract

To support environmental management and differentiated green transformation in industrial parks, this study develops an evaluation framework that assesses eco-industrial development performance and identifies park-specific strengths and weaknesses. The framework contains 39 indicators across economic development, ecological environment, material circulation, resource potential, technological innovation, and policy and management. Weights are derived using the Attribute Hierarchical Model (AHM) and coefficient of variation method, integrated via the minimum-deviation principle, and applied through multi-level grey evaluation to four Chinese parks. Findings show that policy and management is weighted highest, followed by economic development and ecological environment; overall performance ranks Tianjin, Suzhou, Dalian, and Fushun. Critically, similar aggregate performance masks distinct weaknesses in environmental governance, resource circulation, technological innovation, and resource conditions. The framework therefore enables diagnosis of differentiated management priorities and supports park-specific pathways toward eco-industrial development.

Journal of Sustainable DevelopmentVol. 19(6)
Openalex Percentile: Top 15%
Sustainable Industrial Ecology
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