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The Internal Carbon Emissions Reduction Efficiency Of The South African Banking Sector: A Data Envelopment Analysis

机译:南非银行业内部碳减排效率:数据包络分析

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摘要

In this study, a BCC/CCR Data Envelopment Analysis (DEA) Input-Oriented model is employed to measure the carbon reduction efficiency of the four major banks in South Africa (ABSA, Standard Bank, First National Bank, and Nedbank). Specifically, the Banxia Frontier Analysis DEA software is utilized to make two runs on publicly available data. In the first run, number of employees and operating costs are treated as inputs and carbon emissions as the output. In the second run, again, the number of employees and operating costs are treated as inputs, but electricity usage, paper usage, and business travel are treated as outputs. Results are opposite to those generated by the DEA input-oriented model; firms distant from the efficiency frontier are deemed efficient in terms of reducing carbon emissions and firms lying on the efficiency frontier are deemed inefficient. The first run reveals one bank (ABSA) to be inefficient and the second run demonstrates two banks (ABSA and Standard Bank) to be inefficient. Taken in sum, the current research study seeks to facilitate the measurement of carbon reduction efficiency within the banking sector.
机译:在这项研究中,采用BCC / CCR数据包络分析(DEA)投入模型来衡量南非四大银行(ABSA,标准银行,第一国民银行和内德银行)的碳减排效率。具体来说,半夏边境分析DEA软件用于对公开数据进行两次运行。在第一轮中,员工人数和运营成本被视为投入,而碳排放则被视为产出。在第二轮中,再次将员工人数和运营成本视为投入,但将用电量,纸张消耗和商务旅行视为产出。结果与DEA面向输入模型生成的结果相反;在减少碳排放方面,远离效率边界的公司被认为是有效的,而位于效率边界上的公司则被认为是低效率的。第一轮表明一个银行(ABSA)效率低下,第二轮表明两个银行(ABSA和标准银行)效率低下。综上所述,目前的研究旨在促进银行业碳减排效率的衡量。

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