Business School, Sichuan University, Wangjiang Road No. 29, Chengdu, 610064, Republic of China.
Department of Business Administration, National Cheng Kung University, No. 1, University Road, Tainan City, 701, Taiwan, Republic of China.
Environ Sci Pollut Res Int. 2021 Apr;28(16):20093-20110. doi: 10.1007/s11356-020-12037-8. Epub 2021 Jan 6.
The demand for energy has continued to increase because of global economic development, which has led to rising fuel prices and continued pollution problems. China is currently the largest coal consumer and is also the largest emitter of coal-fired CO emissions. However, past efficiency studies have been mostly limited to static analyses and have not considered undesirable outputs. Therefore, this study developed a bound dynamic directional distance function (DDF) data envelopment analysis (DEA) model to explore the energy and environmental efficiencies in 30 Chinese provinces from 2011 to 2015, from which it was found that (1) the overall efficiency was the best in the eastern region, but relatively low in the western region; (2) Beijing, Guangdong, Jiangsu, Shandong, Shanghai, Tianjin, Jiangxi, Jilin, and some other regions had efficiencies of 1; (3) the revenue and non-coal indicator efficiencies were reasonably good, but the expenditure and emissions efficiencies were generally poor; and (4) the key direction for primary improvements was found to be the emissions index.
由于全球经济发展，能源需求持续增长，导致燃料价格上涨和持续的污染问题。中国目前是最大的煤炭消费国，也是最大的燃煤 CO 排放国。然而，过去的效率研究大多局限于静态分析，没有考虑不良产出。因此，本研究开发了一个有界动态方向距离函数（DDF）数据包络分析（DEA）模型，以探讨 2011 年至 2015 年中国 30 个省份的能源和环境效率，研究结果发现：（1）东部地区的综合效率最好，但西部地区相对较低；（2）北京、广东、江苏、山东、上海、天津、江西、吉林等地区的效率为 1；（3）收入和非煤指标效率合理良好，但支出和排放效率普遍较差；（4）主要改进的关键方向被发现是排放指标。
