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A two-stage DEA model for resource allocation in industrial pollution treatment and its application in China

机译:工业污染治理资源分配的两阶段DEA模型及其在中国的应用

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An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers. (C) 2019 Elsevier Ltd. All rights reserved.
机译:越来越多的资源被用于应对中国的污染问题。在当前的技术水平上,衡量和提高这种资源分配的效率是促进污染处理的有效途径。本文利用两阶段数据包络分析(DEA)模型基于零和增益和固定和增益假设来获得分配结果。我们将所有投入分为可自由支配和不可自由支配的投入,并基于环境效率得分构建两个模型来分配资源。使用新模型来计算2011年至2015年中国30个省的绩效和资源分配方案。在使用给定投入资源水平的情况下,大多数省在控制污染排放或处理污染方面效率低下。根据2015年各省的生产可能性集,通过在不同省份之间重新分配污染处理资源,废水和天然气的处理能力可以分别提高1%和3%。本文获得了基于各种假设的环境效率得分和资源分配计划,以启发相应的决策者。 (C)2019 Elsevier Ltd.保留所有权利。

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