{"title":"基准机场效率:数据包络分析的应用","authors":"Tony Diana","doi":"10.2514/ATCQ.14.3.183","DOIUrl":null,"url":null,"abstract":"This article presents a benchmarking methodology designed to help in evaluating the performance of airport operations. It describes how Data Envelopment Analysis (DEA) was used to achieve an efficiency criterion by benchmarking 35 airports based on the percent of on-time gate arrivals. Regression analysis was then used to assess the impact of selected input variables on the likelihood of airport is efficiency. Results show that airport efficiency in terms of operations for the largest 35 airports has continued to decline from 2003 while airport delays and congestion have returned to the levels seen in 2000, when delays were at an all time high.","PeriodicalId":221205,"journal":{"name":"Air traffic control quarterly","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Benchmarking Airport Efficiency: An Application of Data Envelopment Analysis\",\"authors\":\"Tony Diana\",\"doi\":\"10.2514/ATCQ.14.3.183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a benchmarking methodology designed to help in evaluating the performance of airport operations. It describes how Data Envelopment Analysis (DEA) was used to achieve an efficiency criterion by benchmarking 35 airports based on the percent of on-time gate arrivals. Regression analysis was then used to assess the impact of selected input variables on the likelihood of airport is efficiency. Results show that airport efficiency in terms of operations for the largest 35 airports has continued to decline from 2003 while airport delays and congestion have returned to the levels seen in 2000, when delays were at an all time high.\",\"PeriodicalId\":221205,\"journal\":{\"name\":\"Air traffic control quarterly\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Air traffic control quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2514/ATCQ.14.3.183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air traffic control quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/ATCQ.14.3.183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Benchmarking Airport Efficiency: An Application of Data Envelopment Analysis
This article presents a benchmarking methodology designed to help in evaluating the performance of airport operations. It describes how Data Envelopment Analysis (DEA) was used to achieve an efficiency criterion by benchmarking 35 airports based on the percent of on-time gate arrivals. Regression analysis was then used to assess the impact of selected input variables on the likelihood of airport is efficiency. Results show that airport efficiency in terms of operations for the largest 35 airports has continued to decline from 2003 while airport delays and congestion have returned to the levels seen in 2000, when delays were at an all time high.
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