| In recent years,the competition in the air transport market is becoming increasingly fiercer,as well as fuel prices and labor costs have continued to rise.Global airlines have further changed the market structure through mergers and alliances.Airlines are facing a more complex market environment and more severe cost challenges.On the other hand,affected by environmental issues such as global warming,airlines,as large carbon emitters,are also facing increasing pressure to reduce carbon emissions.In order to address aviation carbon emissions,on October 6,2016,a series of resolutions were adopted in the climate change negotiations of the 39 th ICAO Assembly,aiming to implement the "CNG2020 Strategy"(Carbon Neutral Growth from 2020)from 2021 to2035,to achieve Zero growth in net carbon emissions after 2020 in the international aviation industry.The CNG2020 strategy is the first global industry emission reduction market mechanism.Its core is to build a package of global market measures(MBMs)that will have a long-term impact on global aviation companies.Under the severe economic situation and the pressure of carbon emission reduction,airlines must continuously improve their efficiency to achieve sustainable development,control costs while reducing environmental pollution,and improve economic efficiency.In the past,airline efficiency evaluations were mostly based on accurate data for efficiency evaluation.In this paper,considering the inaccuracy of future data,the interval DEA model is used for the first time to calculate the interval efficiency evaluation of airlines,which improve the reliability of prediction.Further research of the influence that CNG2020 strategy to airline efficiency enhances the robustness of the past conclusion.By analyzing the reasons for the high or low efficiency of each airline,this thesis provides guidance and suggestions for each airline to save energy,reduce carbon emissions,and improve environmental efficiency,which will help airlines better respond to the CNG2020 strategy.In the context of the CNG2020 strategy,this thesis takes the efficiency evaluation of airlines as the main research content,and the airline efficiency system is divided into operation phase,service phase and sales phase.BP neural network prediction method is used to predict the airline’s input and output indicators.Interval Network SBM(Slack Based Measure)model of the double frontier is bulit to evaluate the optimistic efficiency,pessimistic efficiency and comprehensive efficiency of 24 global airlines after 2018.Further,by simulating the implementation of CNG2020 strategy and observing the changes in airline efficiency,we analyse the impact of CNG2020 strategy on global airline efficiency.Following important conclusions was drawed.First,optimistic efficiency is more capable for targeting the efficient decision-making-units and stages,but optimistic efficiency cannot determine the inefficient DMUs and stages.While pessimistic efficiency is more capable for finding the inefficient DMUs and stages,but it can not indentify the efficient ones.Second,comprehensive efficiency has stronger discriminative power.Third,interval efficiency value can give more information than precise efficiency value.Forth,only when all the stages efficiency is efficient(or inefficient),the overall efficiency is possible to be efficient(inefficient).Secondly,the comprehensive efficiency integrating the optimistic efficiency and pessimistic efficiency,has a stronger discriminative power,can distinguish effective decision-making-units,and helps to judge the high efficiency stage and the low efficiency stage within the airline system.Thirdly,among the airlines evaluated,EU airlines have relatively high efficiency,while Chinese airlines perform relatively poorly,mainly because Chinese airlines are less efficient in the service and sales stages.Finally,although the CNG2020 strategy has little effect on the overall efficiency of most airlines,it has a more significant impact on the airlines ’operational and sales stages. |
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