{"title":"将空间关系纳入生态效益评价的 DEA 方法:巢湖流域案例研究","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":"{\"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}","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
摘要
本研究介绍了一种创新的数据包络分析(DEA)模型,该模型整合了决策单元(DMU)之间的空间关系,以确定所有变量的相对价格,从而更准确地评估生态效率,尤其是在水资源管理方面。为了更好地反映生态绩效,我们提出了一个包含空间相关性的模型,以解决传统 DEA 模型经常忽略的相互依存问题。通过纳入空间权重矩阵,该模型划定了 DMU 之间的相互作用,提供了一种既考虑技术效率又考虑空间效率影响的综合评价。我们通过对中国长江三角洲重要生态经济区巢湖流域内 17 个国家监测断面的实证分析,证明了我们模型的实用性。这项研究为环境经济学、资源管理和空间分析领域做出了贡献,为可持续环境管理提供了强大的方法框架和可行的见解。
Integrating spatial relationships in the DEA approach for ecological efficiency evaluation: A case study of the Chaohu watershed
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.