臺灣及中國兩岸直航機場經營效率之研究

A STUDY OF THE CROSS-STRAIT DIRECT FLIGHT AIRPORTS’OPERATING EFFICIENCY BETWEEN TAIWAN AND MAINLAND CHINA

蔡麗娟(Li-jane Tsai)

指導教授 ： 陳美芳

大同大學/經營設計學院/事業經營學系所/碩士(2010年)

摘要

本研究選取2007至2008年兩年相同經營型態之臺灣及中國兩岸直航機場共30個機場為研究樣本進行機場經營效率之評估。蒐集樣本使用SPSS統計分析軟體及DEA-Solver電腦軟體進行資料包絡分析、差額變數分析及敏感度分析，將分析結果作為管理者經營機場之參考。本研究使用Charnes et al.(1978)提出的CCR-Out模式來分析兩岸包機直航機場相對效率。採用航空站面積、跑道長度、停機坪數、機場距市中心最近距離、滑行道數為影響機場經營的五個主要投入變數，而以旅客數、起降架次、貨運噸數為三個主要產出變數。

本研究採用方法歸納資料得知結果有四點：一、資料包絡分析：相對效率最佳的機場(效率值=1)有烏魯木齊、桃園國際、深圳、上海浦東、昆明、廣州、重慶、北京、成都共9座。而相對效率最差的機場(效率值<1)在臺灣有臺東、臺中、花蓮、高雄等，中國則有濟南、瀋陽、合肥、天津、福州等，效率有待提昇。二、差額變數分析：分析整體機場長期投入因素，設施使用率最好是「滑行道數」，但設施使用率最差因素是「機場距市中心最近距離」，而機場長期產出因素以「飛機起降次數」需增加幅度較少，「貨運噸數」或「旅客數」大致上經營效率較差需多增加數量。三、敏感度分析：投入因素以「停機坪數」對機場效率具有高度敏感影響，而「跑道長度」及「機場距市中心最短距離」兩個因素影響機場運作最少，產出因素則以「飛機起降次數」對機場效率具有高度影響，而「貨運噸數」影響最少。四、就管理而言CCR效率值未達1的機場，可參考效率值達1的標竿機場，作投入及產出量的調整以提昇效率，昆明機場被參考十五次是最佳的標竿機場。

研究結果對經營效率良好之機場應持續維持，也可再加強提昇整體服務層次。本研究作績效評估最終目的在於解決管理問題，希望運用最少的投入量使得產出量達到最大化以減少機場資源投入浪費，並將研究結果提供予兩岸機場管理單位如交通部、交通部運輸研究所及民航局等單位，作為管理機場營運之參考，且未來再興建新機場時也能併入考量。也希望未來兩岸機場經營能穩健地邁向願景且達成真正提昇效率目標，以增進將來在世界經營之競爭力。

關鍵字

差額變數分析 ； 機場效率 ； 敏感度分析 ； 資料包絡分析

並列摘要

This study selects 30 major airports of the same operation in cross-strait direct flights between Taiwan and China from 2007 to 2008 as the samples for evaluation of airport operational efficiency. We use the SPSS statistical analysis software and DEA-Solver software for data envelopment analysis, slack variable analysis and sensitivity analysis for the data collected. The study result is used as reference for managers in airport operations. The study applies CCR-Output model proposed by Charnes et al. (1978) on the analysis of relative efficiency for airport operations with cross-strait direct charter flights. Five input variables affecting the operation of airports include terminal area, length of runway, number of aprons, number of taxiways, and distance from airport to the nearest urban area; and the three output variables include the number of passengers, number of aircraft movements, and ponds of cargo.

The study used summarized data and obtained the following four results: 1. Data Envelopment Analysis: Nine airports with optimal relative efficiency (CCR value=1) include Urumqi, Taoyuan International, Shenzhen, Shanghai, Pudong, Kunming, Guangzhou, Chongqing, Beijing and Chengdu. Airports with worst relative efficiency (CCR value<1) and require further improvement include Taitung, Taichung, Hualien, and Kaohsiung in Taiwan and Jinan, Shenyang, Hefei, Tianjin, and Fuzhou in mainland China. 2. Slack Variable Analysis: The long-term input variables in the overall airport is analyzed, with the best utilization being “numbers of taxiways” and the worst utilization being the “distance from airport to the nearest urban areas.” With regards to long-term output utilization of airports, the “number of aircraft movements” needs less increase, while “ponds of cargo” or “number of passengers” generally perform poorly and need to be increased in number. 3. Sensitivity Analysis: “number of aprons” has highly sensitive impact on airport efficiency, while “runway length” and "distance from airport to the nearest urban area” have the least impact on airport operation. Output factor such as the “number of aircraft movements” is highly influential on airport efficiency, while “ponds of cargo” has the least impact. 4. With regards to management, airports with CCR value less than 1 may refer to benchmark airports with CCR value greater than 1 for adjustment in input and output productivity, which thereby enhances airport efficiency. Kunming Airport is the benchmark airport which has been referred to15 times.

The study results show that airports with good operational efficiency should be maintained and improved on their overall service standards. The ultimate goal of performance assessment such as in the study is to maximize output with minimal inputs, in order to reduce input waste of airport resources. The results could be used as reference for the department in charge of airport management, such as the Ministry of Transportation, Transportation Research Institute and the Civil Aeronautics Administration. Furthermore, it also provides insights to the future consideration of constructing new airports. In the future, cross-strait airports are expected to steadily move towards their objectives, enhance airport efficiency and improve competitiveness in global management.

並列關鍵字

Airport Efficiency ； Data Envelopment Analysis ； Slack Variable Analysis ； Sensitivity Analysis

參考文獻

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data envelopment analysis combined with principal component analysis