基于超效率SBM模型的航空企业碳排放效率研究

杨扬; 郭挂梅

doi:10.12153/j.issn.1674-991X.20230095

基于超效率SBM模型的航空企业碳排放效率研究

doi: 10.12153/j.issn.1674-991X.20230095

杨扬,
郭挂梅^,

昆明理工大学交通工程学院

详细信息

作者简介:
杨扬（1974—），男，教授，博士，主要从事区域与城市物流规划、跨境运输与国际物流研究，yytongji@163.com

通讯作者:
郭挂梅（1996—），女，硕士研究生，主要从事区域与城市物流规划研究，1046717292@qq.com

中图分类号: X51
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出版历程
- 收稿日期: 2023-02-08
- 录用日期: 2023-06-27
- 网络出版日期: 2023-07-03

Research on carbon emission efficiency of aviation enterprises based on super efficiency SBM model

YANG Yang,
GUO Guamei^,

Faculty of Transportation Engineering, Kunming University of Science and Technology

摘要

摘要:
为识别航空企业碳排放管控水平，采用超效率SBM模型和GML指数模型，研究我国6家航空企业2011—2019年的碳排放效率及其动态变化，并构建面板回归模型探究航空企业碳排放效率的影响因素。结果表明：我国航空企业的碳排放效率在样本年间呈现先下降后上升的“U”形变化趋势；相较于2016年，2019年行业碳排放效率增长6.38%，企业碳排放控制水平有明显提高。碳排放效率变化方面，技术进步与碳排放生产率指数呈现出同方向变化，是碳排放效率提升的主要驱动力；不同企业碳排放效率变化存在较大差异。影响因素方面，客座利用率和燃油成本规制对航空企业碳排放效率有显著的正向影响，当客座利用率和燃油成本规制分别提升1%，碳排放效率分别提升1.524%和0.166%；环境规制对碳排放效率的提升具有积极的影响，现阶段资本结构对碳排放效率具有显著的负向影响，优化企业运营和调整企业资本结构能够在很大程度上促进企业可持续发展。
- 航空运输 /
- 航空企业 /
- 碳排放效率 /
- 超效率SBM模型 /
- 影响因素
Abstract:
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.
- air transportation /
- aviation enterprise /
- carbon emission efficiency /
- super-efficiency SBM model /
- influence factors

HTML全文

图 1 2011—2019年碳排放效率行业均值

Figure 1. Industrial average of carbon emission efficiency from 2011 to 2019

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图 2 2011—2019年的航空企业碳排放效率

Figure 2. Carbon emission efficiency of aviation enterprises from 2011 to 2019

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图 3 航空企业碳排放GML指数及其分解

Figure 3. Carbon emission GML index and decomposition of aviation enterprises

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表 1 2011—2019年南方航空公司5个窗口的碳排放效率

Table 1. Carbon emission efficiency of China Southern Airlines in 5 windows from 2011 to 2019

年份	w1	w2	w3	w4	w5	均值
2011	0.887					0.887
2012	1.002	1.001				1.001
2013	0.812	0.816	0.852			0.827
2014	1.000	0.893	0.887	0.840		0.905
2015	1.017	0.876	0.851	0.797	0.784	0.865
2016		1.012	0.846	0.805	0.797	0.865
2017			1.041	0.859	0.858	0.919
2018				1.049	0.933	0.991
2019					1.049	1.049

下载: 导出CSV

表 2 2011—2019年我国航空公司碳排放效率

Table 2. Carbon emission efficiency of Chinese airlines from 2011 to 2019

年份	国航	东航	南航	海航	春秋航空	吉祥航空	行业均值
2011	1.018	0.895	0.887	0.982	1.138	1.329	1.041
2012	1.017	0.857	1.001	0.975	1.091	1.034	0.996
2013	0.982	0.867	0.827	1.039	0.970	0.895	0.930
2014	0.999	0.841	0.905	1.027	0.962	0.845	0.930
2015	0.941	0.836	0.865	1.061	1.024	0.891	0.936
2016	0.948	0.816	0.865	1.117	0.859	0.971	0.929
2017	0.975	0.775	0.919	1.067	0.897	1.023	0.943
2018	1.048	0.826	0.991	1.066	0.971	1.023	0.988
2019	1.002	0.825	1.049	1.042	1.003	1.010	0.988
历史均值	0.992	0.837	0.923	1.042	0.991	1.002	0.965
排名	3	6	5	1	4	2

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表 3 航空企业碳排放GML指数及分解

Table 3. Carbon emission GML index and decomposition of aviation enterprises

年份	GML	EC	TC
2011—2012	0.890	1.021	0.872
2012—2013	0.947	0.976	0.973
2013—2014	0.991	0.990	1.002
2014—2015	1.038	0.999	1.040
2015—2016	1.005	1.018	0.985
2016—2017	1.034	0.964	1.074
2017—2018	1.056	1.008	1.047
2018—2019	1.037	0.996	1.041
均值	1.000	0.997	1.004

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表 4 不同航空企业碳排放GML指数及分解（2011—2019年）

Table 4. Carbon emission GML index and decomposition of different aviation enterprises (2011-2019)

航空公司	GML	EC	TC
国航	1.000	0.989	1.011
南航	1.024	1.031	0.994
东航	0.989	0.995	0.994
海航	1.008	0.996	1.016
春秋航空	0.990	0.984	1.005
吉祥航空	0.987	0.984	1.005

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表 5 面板回归结果

Table 5. Panel regression results

解释变量	变量含义	系数	T	Prob.
c	常数项	−7.013	−2.509	0.016
$\ln {\rm{util}}$	客座利用率	1.524^**	2.469	0.018
$ \ln {\text{cap}} $	资本结构	−0.106^**	−2.454	0.018
$\ln {\rm{env}}$	环境规制	0.048^**	2.029	0.049
$\ln {\rm{fue}}$	燃油成本规制	0.166^***	3.412	0.001
注：*、分别表示在1%、5%水平显著。R²为0.664；F检验值为9.665。

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