{"title":"Integrating spatial relationships in the DEA approach for ecological efficiency evaluation: A case study of the Chaohu watershed","authors":"Zhixiang Zhou, Mengya Li, Xianzhe Xu, Huaqing Wu","doi":"10.1016/j.ecolind.2024.112868","DOIUrl":null,"url":null,"abstract":"<div><div>This study introduces an innovative Data Envelopment Analysis (DEA) model that integrates spatial relationships among decision-making units (DMUs) to determine relative prices of all variables for evaluating ecological efficiency more accurately, particularly in the context of water resource management. To better capture ecological performance, we propose a model that includes spatial correlation, addressing interdependencies that traditional DEA models often overlook. By incorporating a spatial weight matrix, the model delineates interactions between DMUs, offering a comprehensive evaluation that considers both technical efficiency and the spatial efficiency impact. We demonstrate the utility of our model through an empirical analysis of 17 national monitoring cross-sections within the Chaohu Watershed, a critical ecological and economic zone within China’s Yangtze River Delta. This research contributes to the fields of environmental economics, resource management, and spatial analysis by providing a robust methodological framework and actionable insights for sustainable environmental stewardship.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"169 ","pages":"Article 112868"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X24013256","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study introduces an innovative Data Envelopment Analysis (DEA) model that integrates spatial relationships among decision-making units (DMUs) to determine relative prices of all variables for evaluating ecological efficiency more accurately, particularly in the context of water resource management. To better capture ecological performance, we propose a model that includes spatial correlation, addressing interdependencies that traditional DEA models often overlook. By incorporating a spatial weight matrix, the model delineates interactions between DMUs, offering a comprehensive evaluation that considers both technical efficiency and the spatial efficiency impact. We demonstrate the utility of our model through an empirical analysis of 17 national monitoring cross-sections within the Chaohu Watershed, a critical ecological and economic zone within China’s Yangtze River Delta. This research contributes to the fields of environmental economics, resource management, and spatial analysis by providing a robust methodological framework and actionable insights for sustainable environmental stewardship.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.