| Citation: | YANG Y,GUO G M.Research on carbon emission efficiency of aviation enterprises based on super efficiency SBM model[J].Journal of Environmental Engineering Technology，2023，13（5）：1779-1786 doi: 10.12153/j.issn.1674-991X.20230095
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In order to identify the carbon emission control level of aviation enterprises, the super efficiency SBM model and GML index model were used to study the carbon emission efficiency and dynamic changes of six aviation enterprises in China from 2011 to 2019. Then a panel regression model was constructed to explore the influencing factors of carbon emission efficiency of aviation enterprises. The results showed that the carbon emission efficiency of China's aviation enterprises showed "U" shaped trend of first decreasing and then increasing during the sample period. Compared with 2016, the carbon emission efficiency of the industry increased by 6.38% in 2019, and the level of carbon emission control of enterprises had improved significantly. In terms of changes of carbon emission efficiency, technological progress and productivity index show similar changes in the same direction, which was the main driving force for carbon emission efficiency. There were great differences in the changes of carbon emission efficiency among different enterprises. As for the influencing factors, seat utilization rate and fuel cost regulation had a significantly positive impact on the carbon emission efficiency of aviation enterprises. When the passenger seat utilization and fuel cost regulations were increased by 1%, respectively, the carbon efficiency was improved by about 1.524% and 0.166%, respectively. Environmental regulations had a positive impact on the improvement of carbon emission efficiency. At this stage, the capital structure had a significant negative impact on carbon emission efficiency, and optimizing enterprise operations and adjusting enterprise capital structure could largely promote the sustainable development of enterprises.
| [1] |
CUI Q, LI Y. Evaluating energy efficiency for airlines: an application of VFB-DEA[J]. Journal of Air Transport Management,2015,44/45:34-41. doi: 10.1016/j.jairtraman.2015.02.008
|
| [2] |
LIN B Q, ZHU J P. The role of renewable energy technological innovation on climate change: empirical evidence from China[J]. Science of the Total Environment,2019,659:1505-1512. doi: 10.1016/j.scitotenv.2018.12.449
|
| [3] |
赵宇哲, 周晶淼, 匡海波.欧盟ETS下航空运输企业的能源效率评价研究: 基于时间窗的非径向DEA模型[J]. 管理评论,2015,27(5):38-47.
ZHAO Y Z, ZHOU J M, KUANG H B. Research on airlines enterprises energy efficiency evaluation under EU ETS: based on a non-radial DEA windows model[J]. Management Review,2015,27(5):38-47.
|
| [4] |
张军峰, 方虹, 方思然.环境约束下的中国航空企业环境效率研究[J]. 交通运输系统工程与信息,2017,17(3):243-248.
ZHANG J F, FANG H, FANG S R. Environmental efficiency of China's airlines under environmental constrains[J]. Journal of Transportation Systems Engineering and Information Technology,2017,17(3):243-248.
|
| [5] |
黄赶祥, 景崇毅, 王红岩.碳排放约束下我国航空公司全要素生产率研究[J]. 交通运输系统工程与信息,2018,18(4):19-24.
HUANG G X, JING C Y, WANG H Y. Total factor productivity of China airlines under carbon emission constraints[J]. Journal of Transportation Systems Engineering and Information Technology,2018,18(4):19-24.
|
| [6] |
CHEN Y F, CHENG S Y, ZHU Z T. Exploring the operational and environmental performance of Chinese airlines: a two-stage undesirable SBM-NDEA approach[J]. Journal of Cleaner Production,2021,289:125711. doi: 10.1016/j.jclepro.2020.125711
|
| [7] |
CUI Q, LI Y. Airline energy efficiency measures considering carbon abatement: a new strategic framework[J]. Transportation Research Part D:Transport and Environment,2016,49:246-258. doi: 10.1016/j.trd.2016.10.003
|
| [8] |
WANG Z L, XU X D, ZHU Y F, et al. Evaluation of carbon emission efficiency in China's airlines[J]. Journal of Cleaner Production,2020,243:118500. doi: 10.1016/j.jclepro.2019.118500
|
| [9] |
巩彦峰, 范换利, 刘丹.碳排放约束和技术异质下中国航空公司运输效率研究[J]. 武汉理工大学学报(信息与管理工程版),2018,40(3):289-294.
GONG Y F, FAN H L, LIU D. Research on transport efficiency of Chinese airlines under the restriction of carbon emissions and technology heterogeneity[J]. Journal of Wuhan University of Technology (Information & Management Engineering),2018,40(3):289-294.
|
| [10] |
解文华, 方虹, 张军峰, 等.基于SBM-DEA模型及Malmquist指数的中国与欧盟航空运输企业能源效率比较研究[J]. 数学的实践与认识,2017,47(17):194-201.
XIE W H, FANG H, ZHANG J F, et al. Study on the energy efficiency of China and EU aviation transportation enterprises based on SBM-DEA model and malmquist index[J]. Mathematics in Practice and Theory,2017,47(17):194-201.
|
| [11] |
HADI-VENCHEH A, WANKE P, JAMSHIDI A, et al. Sustainability of Chinese airlines: a modified slack-based measure model for CO2 emissions[J]. Expert Systems,2020,37(3):e12302.
|
| [12] |
XU Y, PARK Y S, PARK J D, et al. Evaluating the environmental efficiency of the US airline industry using a directional distance function DEA approach[J]. Journal of Management Analytics,2021,8(1):1-18. doi: 10.1080/23270012.2020.1832925
|
| [13] |
WU Y Q, HE C Z, CAO X F. The impact of environmental variables on the efficiency of Chinese and other non-Chinese airlines[J]. Journal of Air Transport Management,2013,29:35-38. doi: 10.1016/j.jairtraman.2013.02.004
|
| [14] |
LO P L, MARTINI G, PORTA F, et al. The determinants of CO2 emissions of air transport passenger traffic: an analysis of Lombardy (Italy)[J]. Transport Policy,2020,91:108-119. doi: 10.1016/j.tranpol.2018.11.010
|
| [15] |
TONE K. A slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research,2001,130(3):498-509. doi: 10.1016/S0377-2217(99)00407-5
|
| [16] |
TONE K, TOLOO M, IZADIKHAH M. A modified slacks-based measure of efficiency in data envelopment analysis[J]. European Journal of Operational Research,2020,287(2):560-571. doi: 10.1016/j.ejor.2020.04.019
|
| [17] |
ZHANG Y, WANG W, LIANG L W, et al. Spatial-temporal pattern evolution and driving factors of China's energy efficiency under low-carbon economy[J]. Science of the Total Environment,2020,739:140197. doi: 10.1016/j.scitotenv.2020.140197
|
| [18] |
ZHAO X Y, WANG J W, FU X, et al. Spatial-temporal characteristics and regional differences of the freight transport industry's carbon emission efficiency in China[J]. Environmental Science and Pollution Research,2022,29(50):75851-75869. doi: 10.1007/s11356-022-21101-4
|
| [19] |
刘燕, 张慧.基于偏序集的省际碳排放效率评价[J]. 环境工程技术学报,2022,12(3):937-942. doi: 10.12153/j.issn.1674-991X.20210199
LIU Y, ZHANG H. Evaluation of provincial carbon emission efficiency based on partial order set[J]. Journal of Environmental Engineering Technology,2022,12(3):937-942. doi: 10.12153/j.issn.1674-991X.20210199
|
| [20] |
AVKIRAN N K. Decomposing technical efficiency and window analysis[J]. Studies in Economics and Finance,2004,22(1):61-91. doi: 10.1108/eb043383
|
| [21] |
WU D D, WANG Y H, QIAN W Y. Efficiency evaluation and dynamic evolution of China's regional green economy: a method based on the Super-PEBM model and DEA window analysis[J]. Journal of Cleaner Production,2020,264:121630. doi: 10.1016/j.jclepro.2020.121630
|
| [22] |
YE T F, ZHENG H, GE X Y, et al. Pathway of green development of Yangtze River Economics Belt from the perspective of green technological innovation and environmental regulation[J]. International Journal of Environmental Research and Public Health,2021,18(19):10471. doi: 10.3390/ijerph181910471
|
| [23] |
CHEN X H, GAO Y Y, AN Q X, et al. Energy efficiency measurement of Chinese Yangtze River Delta's cities transportation: a DEA window analysis approach[J]. Energy Efficiency,2018,11(8):1941-1953. doi: 10.1007/s12053-018-9635-7
|
| [24] |
LONG R Y, OUYANG H Z, GUO H Y. Super-slack-based measuring data envelopment analysis on the spatial-temporal patterns of logistics ecological efficiency using global Malmquist Index model[J]. Environmental Technology & Innovation,2020,18:100770.
|
| [25] |
WU J, XIA Q, LI Z Y. Green innovation and enterprise green total factor productivity at a micro level: a perspective of technical distance[J]. Journal of Cleaner Production,2022,344:131070. doi: 10.1016/j.jclepro.2022.131070
|
| [26] |
CUI Q. Investigating the airlines emission reduction through carbon trading under CNG2020 strategy via a Network Weak Disposability DEA[J]. Energy,2019,180:763-771. doi: 10.1016/j.energy.2019.05.159
|
| [27] |
ZHENG Z L. Energy efficiency evaluation model based on DEA-SBM-Malmquist index[J]. Energy Reports,2021,7:397-409. doi: 10.1016/j.egyr.2021.10.020
|
| [28] |
HILEMAN J I, deLa ROSA BLANCO E, BONNEFOY P A, et al. The carbon dioxide challenge facing aviation[J]. Progress in Aerospace Sciences,2013,63:84-95. doi: 10.1016/j.paerosci.2013.07.003
|
| [29] |
RYERSON M S, HANSEN M, BONN J. Time to burn: flight delay, terminal efficiency, and fuel consumption in the National Airspace System[J]. Transportation Research Part A:Policy and Practice,2014,69:286-298. doi: 10.1016/j.tra.2014.08.024
|
| [30] |
CHAO H, AGUSDINATA D B, DeLAURENTIS D, et al. Carbon offsetting and reduction scheme with sustainable aviation fuel options: fleet-level carbon emissions impacts for US airlines[J]. Transportation Research Part D:Transport and Environment,2019,75:42-56. ⊗ doi: 10.1016/j.trd.2019.08.015
|
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