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Evaluating the environmental efficiency of the U.S. airline industry using a directional distance function DEA approach
Journal of Management Analytics ( IF 3.6 ) Pub Date : 2020-10-21 , DOI: 10.1080/23270012.2020.1832925
Yuan Xu 1 , Yong Shin Park 2 , Ju Dong Park 3 , Wonjoo Cho 4
Affiliation  

This study applies a directional distance function (DDF) data envelopment analysis (DEA) model to measure the environmental efficiency of 12 U.S. airlines 2013–2016 by considering flight delay and greenhouse gas (GHG) emissions as joint undesirable outputs. First, the environmental efficiency of airlines is compared using the CCR DEA (without flight delay) and DDF DEA (with flight delay). We find that several airlines experienced substantial changes in environmental efficiency scores when flight delay is considered. Secondly, a tobit regression is used to explore whether the environmental factors of fleet age, ownership type, freight traffic, market share, and carrier type affect airlines’ environmental efficiency. The results demonstrate that all of these factors significantly influence airline performance.



中文翻译:

使用方向距离函数DEA方法评估美国航空业的环境效率

本研究应用方向距离函数(DDF)数据包络分析(DEA)模型,通过将航班延误和温室气体(GHG)排放视为共同的不良输出,来衡量2013年至2016年美国12家航空公司的环境效率。首先,使用CCR DEA(无航班延误)和DDF DEA(有航班延误)比较航空公司的环境效率。我们发现,考虑到航班延误,几家航空公司的环境效率得分发生了重大变化。其次,采用轨道回归法研究机队年龄,所有权类型,货运量,市场份额和承运人类型等环境因素是否影响航空公司的环境效率。结果表明,所有这些因素均会显着影响航空公司的绩效。

更新日期:2020-10-21
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