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)emiss...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.展开更多
文摘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.
