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基于DEA的矿业生态效率评价与影响因素研究
Evaluation and Influencing Factors of Mining Ecological Efficiency Based on DEA

DOI: 10.12677/sa.2024.136239, PP. 2472-2485

Keywords: 数据包络算法,生态效率,绿色矿业,评价模型
Data Envelopment Algorithm
, Ecological Efficiency, Green Mining, Evaluation Model

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Abstract:

本文利用数据包络算法的CCR模型、非期望产出SBM模型以及Malmquist指数法进行了省域尺度发展效率测度,计算了中国27个省域单元的矿产资源开发效率,并借助于描述性统计方法和象限图,开展了区域的异质性分析。以探究绿色矿业发展空间差异,Tobit模型用于研究影响绿色矿业发展的主要因素,并根据实证分析的结果提出提升中国绿色矿业发展水平的政策建议。以往的研究主要是从生态经济学角度对某个产业进行定量的静态研究,本研究是进行的动态研究。构建矿业生态经济效率的评价模型,并据此对中国矿业生态经济效率进行评价,以期准确把握中国矿业生态经济的运行状况,为中国矿业的管理和规划提供实证支撑,促进矿业与生态、社会的协调可持续发展。
This paper uses the CCR model of data envelopment algorithm, the non-expected output SBM model and the Malmquist index method to measure the development efficiency at the provincial scale, calculates the mineral resource development efficiency of 27 provincial units in China, and conducts regional heterogeneity analysis with the help of descriptive statistical methods and quadrant diagrams. In order to explore the spatial differences in the development of green mining, the Tobit model is used to study the main factors affecting the development of green mining, and based on the results of empirical analysis, policy recommendations for improving the level of development of China’s green mining are proposed. Previous studies mainly conducted quantitative static research on a certain industry from the perspective of ecological economics, while this study is a dynamic study. An evaluation model for the ecological and economic efficiency of mining is constructed, and based on this, the ecological and economic efficiency of China’s mining industry is evaluated, in order to accurately grasp the operating status of China’s mining ecological economy, provide empirical support for the management and planning of China’s mining industry, and promote the coordinated and sustainable development of mining, ecology and society.

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