衡量中国能源市场的碳排放绩效:改进的非径向定向距离函数数据包络分析的证据

IF 6 2区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Yinghao Pan, Jie Wu, Chao-Chao Zhang, Muhammad Ali Nasir
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引用次数: 0

摘要

能源市场面临的最复杂挑战是找到有效的解决方案,以减少二氧化碳排放 (CE) 并提高环境绩效 (EP)。电力行业的煤炭生产是这些排放的主要来源。在本研究中,我们开发了一个新颖的线性规划模型,该模型考虑了不良产出,以评估华东地区 15 家电力企业 2016 年至 2020 年的环境绩效。此外,我们还采用了全球非径向马尔基斯特-伦伯格生产率指数(GNML)来分析这些企业效率变化的影响机制。我们的研究结果表明,虽然华东地区电力行业的生产效率有所提高,但仍处于相对较低的水平,并表现出不稳定性。此外,技术效率(TE)和规模效率(SE)在决定该行业的生产效率方面发挥着重要作用。因此,行业管理者有必要实施标准化的生产管理规定,加强技术开发和规模投资,并加强对意外排放的控制,从而促进能源转型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring carbon emission performance in China's energy market: Evidence from improved non-radial directional distance function data envelopment analysis
The most complex challenge facing the energy market is identifying effective solutions to reduce CO2 emissions (CEs) and enhance environmental performance (EP). Coal production within the power sector is the primary source of these emissions. In this study, we developed a novel linear programming model that accounts for undesirable outputs to assess the EP of 15 power enterprises in eastern China from 2016 to 2020. In addition, we employed a global non-radial Malmquist-Luenberger productivity index (GNML) to analyse the mechanisms influencing changes in efficiency among these enterprises. Our findings indicate that, while the EP of the power industry in eastern China improved, it remains at a relatively low level and exhibits instability. Moreover, technological efficiency (TE) and scale efficiency (SE) play a significant role in determining production efficiency within the sector. Therefore, it is essential for industry managers to implement standardized production management regulations, enhance technological development and scale investments, and strengthen control over unintended emissions that could facilitate energy transition.
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来源期刊
European Journal of Operational Research
European Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
11.90
自引率
9.40%
发文量
786
审稿时长
8.2 months
期刊介绍: The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.
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