An Empirical Study on Environmental Efficiency Measurements and Influencing Factors

Chen, Yuxiu; Li, Long; Yu, Jian; Tsai, Sang-Bing; Wang, Jiangtao

doi:10.2478/eces-2020-0033

Abstract

Airlines are an important part of the comprehensive transportation system. Therefore, it is of great practical significance to empirically analyse the measurement of airlines’ environmental efficiency and influencing factors. Adopting the SBM-DEA model, this study measured the environmental efficiency of 20 Chinese airlines between 2010 and 2017 and empirically analysed the factors influencing their environmental efficiency using a Tobit regression model. Spring Airlines, China Southern Airlines, and Hainan Airlines were found to have the highest environmental efficiency. Tianjin Airlines, Hebei Airlines, and China Express Airlines had the lowest environmental efficiency. The Tobit regression results showed that average flight distance, load factor, market share, and proportion of cargo and mail turnover had a significant positive effect on airline environmental efficiency. Fuel consumption per ton-km had a significant negative effect on airline environmental efficiency.

References

[l] Ma XM, Zhang C, Xiong SQ, Tian YS. Environmental efficiency and factors analysis of industry sector in china: an empirical analysis based on super-SBM. Ecol Economy. 2018;34(11):96-102. http://www.cnki.com.cn/Article/CJFDTOTAL-STJJ201811018.htm.
Search in Google Scholar Back to article
[2] Lin RJ. Using fuzzy DEMATEL to evaluate the green supply chain management practices. J Clean Prod. 2013;40:32-9. DOI: 10.1016/j.jclepro.2011.06.010.10.1016/j.jclepro.2011.06.010
Search in Google Scholar Back to article
[3] Chen J, Cheng JH, Sheng, Dai S. Regional eco-innovation in China: an analysis of eco-innovation levels and influencing factors. J Clean Prod. 2017;153:1-14. DOI: 10.1016/j.jclepro.2017.03.141.10.1016/j.jclepro.2017.03.141
Search in Google Scholar Back to article
[4] Guan JC, Chen KH. Measuring the innovation production process: a cross-region empirical study of China’s high-tech innovation. Technovation. 2010;30:348-58. DOI: 10.3923/itj.2011.1484.1497.10.3923/itj.2011.1484.1497
Search in Google Scholar Back to article
[5] Sun LY, Miao CL, Li Y. Ecological-economic efficiency evaluation of green technology innovation in strategic emerging industries based on entropy weighted TOPSIS method. Ecol Indicators. 2017;73:554-8. DOI: 10.1016/j.ecolind.2016.10.018.10.1016/j.ecolind.2016.10.018
Search in Google Scholar Back to article
[6] Liang XD, Si DY, Zhang XL. Regional sustainable development analysis based on information entropy-Sichuan province as an example. Int J Environ Res Public Health. 2017;14(10):1219. DOI: 10.3390/ijerph14101219.10.3390/ijerph14101219566472029027982
Search in Google Scholar Back to article
[7] Sun P, Song LF. Calculation of China's marine environmental efficiency based on undesired super efficiency-Malmquist Model. China Population, Resour Environ. 2019;29(02):43-51. DOI: 10.12062/cpre.20180722.
Search in Google Scholar Back to article
[8] Chen L, Wang YM. Environmental efficiency of China's transportation industry from the perspective of technological differences. J Transport Systems Eng Inform Technol. 2018;18(06):22-7. DOI: 10.16097/j.cnki.1009-6744.2018.06.004.
Search in Google Scholar Back to article
[9] Li L, Li JS, Jiang ZL. Evolution and genetic mechanism of resource environmental efficiency pattern in central China based on SBM-DEA model. Resources and Environment in the Yangtze Basin. 2017;26(11):1761-73. DOI: 10.11870/cjlyzyyhj201711005.
Search in Google Scholar Back to article
[10] Guo SD, Tong M, Guo J. Measurement and influencing factors of inter-provincial real environmental efficiency based on three-stage DEA model. China Population, Resour Environ. 2018;28(3):106-16. DOI: 10.12062/cpre.20170917.
Search in Google Scholar Back to article
[11] Zou B, Elke M, Hansen M, Kafle N. Evaluating air carrier fuel efficiency in the US airline industry. Transportation Res Part A: Policy Practice. 2014;59(1):306-30. DOI: 10.1016/j.tra.2013.12.003.10.1016/j.tra.2013.12.003
Search in Google Scholar Back to article
[12] Tone K. Dealing with undesirable outputs in DEA: A slacks-based measure (SBM) approach. Tokyo: National Graduate Institute for Policy Studies, 2003. Available from: https://www.researchgate.net/publication/284047010_Dealing_with_undesirable_outputs_in_DEA_a_Slacks-Based_Measure_SBM_approach.
Search in Google Scholar Back to article
[13] Cui Q, Li Y. Airline energy efficiency measures considering carbon abatement: A new strategic framework. Transportation Res Part D. 2016;49:246-58. DOI: 10.1016/j.trd.2016.10.003.10.1016/j.trd.2016.10.003
Search in Google Scholar Back to article
[14] Chang YT, Park HS, Jeong JB. Evaluating economic and environmental efficiency of global airlines: A SBM-DEA approach. Transportation Res Part D. 2014;27(03):46-50. DOI: 10.1016/j.trd.2013.12.013.10.1016/j.trd.2013.12.013
Search in Google Scholar Back to article
[15] Jain RK, Natarajan R. A DEA study of airlines in India. Asia Pacific Manage Rev. 2015;20(4):285-92. DOI: 10.1016/j.apmrv.2015.03.004.10.1016/j.apmrv.2015.03.004
Search in Google Scholar Back to article
[16] Zhao YZ, Zhou JW, Yan HB. Research on airlines enterprises energy efficiency evaluation under EU ETS: Based on a non-radial DEA windows model. Manage Rev. 2015;27(05):38-47. DOI: 10.14120/j.cnki.cn11-5057/f.2015.05.005.
Search in Google Scholar Back to article
[17] Su WZ, Li H. The industrial environmental efficiency and its influencing factors of “One Belt and One Road”. Sci Technol Progress Policy. 2018;35(19):155-60. DOI: 10.6049/kjjbydc.2018050784.
Search in Google Scholar Back to article
[18] Hong S, Zhang A. An efficiency study of airlines and air cargo/passenger divisions: a DEA approach. World Rev Int Transportation Res. 2010;3(1/2):137-49. DOI: 10.1504/WRITR.2010.031584.10.1504/WRITR.2010.031584
Search in Google Scholar Back to article
[19] Zhang JF, Fang H. Energy efficiency of airlines and its influencing factors: A comparison between China and the United States. Resources, Conserv Recycling. 2017;125(4):1-8. DOI: 10.1016/j.resconrec.2017.05.007.10.1016/j.resconrec.2017.05.007
Search in Google Scholar Back to article
[20] Christoph PK, Javier CH, Pablo DR, Barroso C, Javier F. Diversity of eco-innovations: a quantitative approach. J Cleaner Prod. 2017;166:1494-506. DOI: 10.1016/j.jclepro.2017.07.241.10.1016/j.jclepro.2017.07.241
Search in Google Scholar Back to article
[21] Żuk O, Kosior G, Oloś G. Characteristics of acute toxicity dynamics of selected toxicants on aquatic crustaceans. Ecol Chem Eng S. 2019;26(2):397-408. DOI: 10.1515/eces-2019-0028.10.1515/eces-2019-0028
Search in Google Scholar Back to article
[22] Sołowski G, Konkol I, Cenian A. Perspectives of hydrogen production from corn wastes in Poland by means of dark fermentation. Ecol Chem Eng S. 2019;26(2):255-263. DOI: 10.1515/eces-2019-0031.10.1515/eces-2019-0031
Search in Google Scholar Back to article
[23] Bhore SJ. Paris agreement on climate change: a booster to enable sustainable global development and beyond. Int J Environ Res Public Health. 2016;13:1134. DOI: 10.3390/ijerph13111134.10.3390/ijerph13111134512934427854248
Search in Google Scholar Back to article
[24] Marszałek M, Kowalski Z, Makara A. The possibility of contamination of water-soil environment as a result of the use of pig slurry. Ecol Chem Eng S. 2019;26(2):313-30. DOI: 10.1515/eces-2019-0022.10.1515/eces-2019-0022
Search in Google Scholar Back to article
[25] Huang G, Ali S. Local sustainability and gender ratio: evaluating the impacts of mining and tourism on sustainable development in Yunnan, China. Int J Environ Res Public Health. 2015;12:927-39. DOI: 10.3390/ijerph120100927.10.3390/ijerph120100927430690225607602
Search in Google Scholar Back to article
[26] Ali M, Cantner U, Roy I. Knowledge spillovers through FDI and trade: the moderating role of quality-adjusted human capital. J Evolutionary Economics. 2015;26(4):1-32. DOI: 10.1007/s00191-016-0462-8.10.1007/s00191-016-0462-8
Search in Google Scholar Back to article
[27] Ghosh D, Shah J. A comparative analysis of greening policies across supply chain structures. Int J Prod Economics. 2012;135(2):568-83. DOI: 10.1016/j.ijpe.2011.05.027.10.1016/j.ijpe.2011.05.027
Search in Google Scholar Back to article
[28] Ghosh D, Shah J. Supply chain analysis under green sensitive consumer demand and cost sharing contract. Int J Prod Economics. 2015;164:319-29. DOI: 10.1016/j.ijpe.2014.11.005.10.1016/j.ijpe.2014.11.005
Search in Google Scholar Back to article
[29] Esfahbodi A, Zhang Y, Watson G. Sustainable supply chain management in emerging economies: Trade-offs between environmental and cost performance. Int J Prod Economics. 2016;181:350-66. DOI: 10.1016/j.ijpe.2016.02.013.10.1016/j.ijpe.2016.02.013
Search in Google Scholar Back to article

An Empirical Study on Environmental Efficiency Measurements and Influencing Factors

Abstract

Paradigm

My account