2단계 네트워크 DEA모형을 이용한 저비용항공사 점유율이 공항효율성에 미치는 영향
An Analysis on Effects of Low Cost Carrier to Global Major Airports Using Two-Stage Network DEA Model
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저비용항공사와 공항 효율성의 관계를 분석한 대부분의 선행연구는 DEA 분석을 통해 개별적으로 평가하는 방식으로 수행되었다. 이에 따라 공항의 프로세스가 하나의 블랙박스로 간주되어 비효율성이 공항 내 어느 단계에서 발생하는지에 대한 분석에 한계가 있었다. 본 연구는 2단계 네트워크 분석을 사용하여 공항의 효율성을 세분화하여 저비용항공사가 미치는 영향을 분석하였다. 네트워크 DEA는 기존 DEA 모델의 단점을 보완하는 방법으로 중간과정에서 발견하지 못한 부분을 세분화해서 설명할 수 있다. 공항의 효율성 분석은 공항의 프로세스를 인프라, 인력 투입 등을 통해 여객, 화물 등을 산출하는 운영단계와 운영단계에서의 산출물을 활용하여 재무적 수익으로 전환하는 수익단계 2단계로 구조화하여 측정하였다. 실증분석을 위해서 아태, 북미, 유럽의 세계주요공항 128개 공항을 분석 대상으로 하였고, 분석 기간은 2015년부터 2019년까지이다. 네트워크 DEA 모형의 1단계 투입변수는 활주로수, 터미널면적, 종업원수, 운영비용이고, 산출변수는 여객, 화물, 운항횟수이다. 2단계 투입요소는 1단계 산출요소를 투입요소로 하고 산출요소는 순영업이익을 사용하였다. 분석 결과 LCC 취항에 따른 운영효율성은 U자형으로 항공사 점유율이 특정 비율(40%) 이상이 되면 (+) 값을 갖는 것으로 나타났다. 수익효율성은 (-)값으로 나타났다. 전체효율성도 (-) 값으로 나타났는데, 이는 수익효율성의 (-)값이 운영효율성의 (+) 값을 상쇄시켰기 때문으로 판단된다. 네트워크 DEA를 활용하여 그동안 밝혀지지 않았던 중간과정의 효율성 분석이 가능하고, 결과를 기반으로 어떤 부분에서 공항의 효율성을 개선해야 하는지에 대한 실무적인 시사점을 얻을 수 있다.
Abstract
Most previous studies have focused on examining the relationship between low-cost airlines and airport efficiency by individually evaluating airport efficiency through DEA analysis. Accordingly, the airport’s process has been viewed as a black box, and there have been limitations in analyzing at what stage within the airport inefficiency occurs. This study used two-stage network analysis to segment airport efficiency and analyze the correlation with low-cost airlines. Network DEA is a method that avoids the shortcomings of the traditional DEA model and can illustrate efficiency in detail by decomposing hidden processes in the intermediate process. The airport’s efficiency evaluation was measured by structuring the airport’s process into two stages: the operation stage, which handles passengers and cargo through infrastructure and manpower input, and theprofit stage, which converts the output from the operation stage into financial profits. For the empirical analysis, 128 global major airports in Asia Pacific, North America, and Europe were selected, and the analysis period was from 2015 to 2019. The first stage input variables of the network DEA model are the number of runways, terminal area, number of employees, and operating costs, and the output variables are passengers, cargo, and number of flights. The second-stage input factors used the first-stage output factors as input factors, and net operating income was used as the output factor. As a result of the analysis, it was found that the operational efficiency achieved by LCC service is U-shaped and has a positive value when the airline’s market share exceeds a certain ratio (40%). Profit efficiency was shown as a (-) value. The overall efficiency also appeared as a (-) value, which is believed to be because the (-) value of revenue efficiency offset the (+) value of operating efficiency. By using network DEA, it has become possible to analyze intermediate processes that were previously hidden as black boxes, allowing airports to see in which areas they need to improve efficiency.
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